This paper addresses the accuracy and timeliness limitations of traditional comprehensive prediction methods by proposing an approach of decision-level fusion of multisource data.A risk prediction indicator system was...This paper addresses the accuracy and timeliness limitations of traditional comprehensive prediction methods by proposing an approach of decision-level fusion of multisource data.A risk prediction indicator system was established for water and mud inrush in tunnels by analyzing advanced prediction data for specifi c tunnel segments.Additionally,the indicator weights were determined using the analytic hierarchy process combined with the Huber weighting method.Subsequently,a multisource data decision-layer fusion algorithm was utilized to generate fused imaging results for tunnel water and mud inrush risk predictions.Meanwhile,risk analysis was performed for different tunnel sections to achieve spatial and temporal complementarity within the indicator system and optimize redundant information.Finally,model feasibility was validated using the CZ Project Sejila Mountain Tunnel segment as a case study,yielding favorable risk prediction results and enabling effi cient information fusion and support for construction decision-making.展开更多
This research investigates the application of multisource data fusion using a Multi-Layer Perceptron (MLP) for Human Activity Recognition (HAR). The study integrates four distinct open-source datasets—WISDM, DaLiAc, ...This research investigates the application of multisource data fusion using a Multi-Layer Perceptron (MLP) for Human Activity Recognition (HAR). The study integrates four distinct open-source datasets—WISDM, DaLiAc, MotionSense, and PAMAP2—to develop a generalized MLP model for classifying six human activities. Performance analysis of the fused model for each dataset reveals accuracy rates of 95.83 for WISDM, 97 for DaLiAc, 94.65 for MotionSense, and 98.54 for PAMAP2. A comparative evaluation was conducted between the fused MLP model and the individual dataset models, with the latter tested on separate validation sets. The results indicate that the MLP model, trained on the fused dataset, exhibits superior performance relative to the models trained on individual datasets. This finding suggests that multisource data fusion significantly enhances the generalization and accuracy of HAR systems. The improved performance underscores the potential of integrating diverse data sources to create more robust and comprehensive models for activity recognition.展开更多
Video imagery enables both qualitative characterization and quantitative retrieval of low-visibility conditions.These phenomena exhibit complex nonlinear dependencies on atmospheric processes,particularly during moist...Video imagery enables both qualitative characterization and quantitative retrieval of low-visibility conditions.These phenomena exhibit complex nonlinear dependencies on atmospheric processes,particularly during moisture-driven weather events such as fog,rain,and snow.To address this challenge,we propose a dual-branch neural architecture that synergistically processes optical imagery and multi-source meteorological data(temperature,humidity,and wind speed).The framework employs a convolutional neural network(CNN)branch to extract visibility-related visual features from video imagery sequences,while a parallel artificial neural network(ANN)branch decodes nonlinear relationships among the meteorological factors.Cross-modal feature fusion is achieved through an adaptive weighting layer.To validate the framework,multimodal Backpropagation-VGG(BP-VGG)and Backpropagation-ResNet(BP-ResNet)models are developed and trained/tested using historical imagery and meteorological observations from Nanjing Lukou International Airport.The results demonstrate that the multimodal networks reduce retrieval errors by approximately 8%–10%compared to unimodal networks relying solely on imagery.Among the multimodal models,BP-ResNet exhibits the best performance with a mean absolute percentage error(MAPE)of 8.5%.Analysis of typical case studies reveals that visibility fluctuates rapidly while meteorological factors change gradually,highlighting the crucial role of high-frequency imaging data in intelligent visibility retrieval models.The superior performance of BP-ResNet over BP-VGG is attributed to its use of residual blocks,which enables BP-ResNet to excel in multimodal processing by effectively leveraging data complementarity for synergistic improvements.This study presents an end-to-end intelligent visibility inversion framework that directly retrieves visibility values,enhancing its applicability across industries.However,while this approach boosts accuracy and applicability,its performance in critical low-visibility scenarios remains suboptimal,necessitating further research into more advanced retrieval techniques—particularly under extreme visibility conditions.展开更多
The construction of human settlements plays a vital role in achieving sustainable development goals.With the growing population,both urban and rural planning—as well as the development of human settlements—on the Qi...The construction of human settlements plays a vital role in achieving sustainable development goals.With the growing population,both urban and rural planning—as well as the development of human settlements—on the Qinghai-Tibet Plateau in China have received increasing attention.This study proposed a comprehensive framework to assess the quality of human settlements and identify their limiting factors of Nyingchi City,southeastern Qinghai-Tibet Plateau of China.The framework integrated a region-specific evaluation system tailored to the plateau’s unique characteristics and utilized multi-source data collected through field-based questionnaires and remote sensing.Analytical methods employed include the Criteria Importance Through Intercriteria Correlation(CRITIC)weighting method,difference analysis for evaluating spatial and categorical variations,and a novel approach introduced in this study for identifying limiting factors.In August 2021,a questionnaire-based survey was conducted in the southeastern Qinghai-Tibet Plateau,yielding 823 valid responses.The average evaluation score for human settlement quality(HSQ)was(6.96±0.94),indicating that settlement conditions were approaching the satisfaction threshold.Notably,the score for the health dimension was(6.28±1.41),reflecting relatively underdeveloped health services in the region.From the perspective of spatial patterns,despite its favorable natural conditions,the HSQ in Medog County was relatively backward,reflecting uncoordinated development that warrants attention.Significant differences were observed in the perceptions of human settlements among different groups in terms of ethnicity,income,and educational background.Low ratings for income and employment conditions represented a major limitation to the local HSQ.The development of human settlements in the southeastern Qinghai-Tibet Plateau still needs further promotion due to population disparities and the challenges of creating a healthy environment in high-altitude regions.The results are valuable for improving human settlements in plateau regions,which can help make targeted policy recommendations.展开更多
To meet the increasing demand of national spatial database infrastructure construction and application, a concept model of China's coastal zone scientific data platform is established based on the information feat...To meet the increasing demand of national spatial database infrastructure construction and application, a concept model of China's coastal zone scientific data platform is established based on the information feature analysis of a compound dataset, consisting of remote sensing data and conventional data. Based on this concept model, the detailed logical database structure and the storage strategy of remote sensing data and their metadata using ArcSDE are designed. The complicated technology of multisources data combination in this research is crucial to the future coastal zone and offshore database construction and practical running, which will provide intelligent information analysis and technological service for coastal zone and offshore investigation, research, development and management.展开更多
The karst mountainous area is an ecologically fragile region with prominent humanland contradictions.The resource-environment carrying capacity(RECC)of this region needs to be further clarified.The development of remo...The karst mountainous area is an ecologically fragile region with prominent humanland contradictions.The resource-environment carrying capacity(RECC)of this region needs to be further clarified.The development of remote sensing(RS)and geographic information system(GIS)provides data sources and processing platform for RECC monitoring.This study analyzed and established the evaluation index system of RECC by considering particularity in the karst mountainous area of Southwest China;processed multisource RS data(Sentinel-2,Aster-DEM and Landsat-8)to extract the spatial distributions of nine key indexes by GIS techniques(information classification,overlay analysis and raster calculation);proposed the methods of index integration and fuzzy comprehensive evaluation of the RECC by GIS;and took a typical area,Guangnan County in Yunnan Province of China,as an experimental area to explore the effectiveness of the indexes and methods.The results showed that:(1)The important indexes affecting the RECC of karst mountainous area are water resources,tourism resources,position resources,geographical environment and soil erosion environment.(2)Data on cultivated land,construction land,minerals,transportation,water conservancy,ecosystem services,topography,soil erosion and rocky desertification can be obtained from RS data.GIS techniques integrate the information into the RECC results.The data extraction and processing methods are feasible on evaluating RECC.(3)The RECC of Guangnan County was in the mid-carrying level in 2018.The midcarrying and low-carrying levels were the main types,accounting for more than 80.00%of the total study area.The areas with high carrying capacity were mainly distributed in the northern regions of the northwest-southeast line of the county,and other areas have a low carrying capacity comparatively.The coordination between regional resource-environment status and socioeconomic development is the key to improve RECC.This study explores the evaluation index system of RECC in karst mountainous area and the application of multisource RS data and GIS techniques in the comprehensive evaluation.The methods can be applied in related fields to provide suggestions for data/information extraction and integration,and sustainable development.展开更多
Crop root system plays an important role in the water cycle of the soil-plant-atmosphere continuum. In this study, com- bined isotope techniques, root length density and root cell activity analysis were used to invest...Crop root system plays an important role in the water cycle of the soil-plant-atmosphere continuum. In this study, com- bined isotope techniques, root length density and root cell activity analysis were used to investigate the root water uptake mechanisms of winter wheat （Triticum aesfivum L.） under different irrigation depths in the North China Plain. Both direct inference approach and multisource linear mixing model were applied to estimate the distribution of water uptake with depth in six growing stages. Results showed that winter wheat under land surface irrigation treatment （Ts） mainly absorbed water from 10-20 cm soil layers in the wintering and green stages （66.9 and 72.0%, respectively）; 0-20 cm （57.0%） in the jointing stage; 0-40 （15.3%） and 80-180 cm （58.1%） in the heading stage; 60-80 （13.2%） and 180-220 cm （35.5%） in the filling stage; and 0-40 （46.8%） and 80-100 cm （31.0%） in the ripening stage. Winter wheat under whole soil layers irrigation treatment （Tw） absorbed more water from deep soil layer than Ts in heading, filling and ripening stages. Moreover, root cell activity and root length density of winter wheat under TW were significantly greater than that of Ts in the three stages. We concluded that distribution of water uptake with depth was affected by the availability of water sources, the root length density and root cell activity. Implementation of the whole soil layers irrigation method can affect root system distribution and thereby increase water use from deeper soil and enhance water use efficiency.展开更多
We developed a forest type classification technology for the Daxing＇an Mountains of northeast China using multisource remote sensing data.A SPOT-5 image and two temporal images of RADARSAT-2 full-polarization SAR wer...We developed a forest type classification technology for the Daxing＇an Mountains of northeast China using multisource remote sensing data.A SPOT-5 image and two temporal images of RADARSAT-2 full-polarization SAR were used to identify forest types in the Pangu Forest Farm of the Daxing＇an Mountains.Forest types were identified using random forest（RF） classification with the following data combination types： SPOT-5 alone,SPOT-5 and SAR images in August or November,and SPOT-5 and two temporal SAR images.We identified many forest types using a combination of multitemporal SAR and SPOT-5 images,including Betula platyphylla,Larix gmelinii,Pinus sylvestris and Picea koraiensis forests.The accuracy of classification exceeded 88% and improved by 12% when compared to the classification results obtained using SPOT data alone.RF classification using a combination of multisource remote sensing data improved classification accuracy compared to that achieved using single-source remote sensing data.展开更多
High-quality and high-resolution precipitation data are the basis for mesoscale numerical weather forecasting,model verification,and hydrological monitoring,which play an important role in meteorological and hydrologi...High-quality and high-resolution precipitation data are the basis for mesoscale numerical weather forecasting,model verification,and hydrological monitoring,which play an important role in meteorological and hydrological disaster prevention and mitigation.In this study,high-density rain gauge data are used to evaluate the fusion accuracy of the China Meteorological Administration Multisource Precipitation Analysis System(CMPAS),and four CMPAS products with different spatial and temporal resolution and different data sources are compared,to derive the applicability of CMPAS.Results show that all the CMPAS products show high accuracy in the Sichuan Basin,followed by Panxi Area and the western Sichuan Plateau.The errors of the four products all rise with the increase in precipitation.CMPAS overestimates precipitation in summer and autumn and underestimates it in spring and winter.Overall,the applicability of these fused data in the Sichuan Basin is quite good.Due to the lack of observations and the influence of the terrain and meteorological conditions,the evaluation of CMPAS in the plateau area needs further analysis.展开更多
Single gimbal control moment gyroscope(SGCMG)with high precision and fast response is an important attitude control system for high precision docking,rapid maneuvering navigation and guidance system in the aerospace f...Single gimbal control moment gyroscope(SGCMG)with high precision and fast response is an important attitude control system for high precision docking,rapid maneuvering navigation and guidance system in the aerospace field.In this paper,considering the influence of multi-source disturbance,a data-based feedback relearning(FR)algorithm is designed for the robust control of SGCMG gimbal servo system.Based on adaptive dynamic programming and least-square principle,the FR algorithm is used to obtain the servo control strategy by collecting the online operation data of SGCMG system.This is a model-free learning strategy in which no prior knowledge of the SGCMG model is required.Then,combining the reinforcement learning mechanism,the servo control strategy is interacted with system dynamic of SGCMG.The adaptive evaluation and improvement of servo control strategy against the multi-source disturbance are realized.Meanwhile,a data redistribution method based on experience replay is designed to reduce data correlation to improve algorithm stability and data utilization efficiency.Finally,by comparing with other methods on the simulation model of SGCMG,the effectiveness of the proposed servo control strategy is verified.展开更多
Sludge is the by-product of wastewater treatment process. Multisource sludge can be defined as sludge from different sources. Based on the sludge properties of five typical cities in the Yangtze River basin, including...Sludge is the by-product of wastewater treatment process. Multisource sludge can be defined as sludge from different sources. Based on the sludge properties of five typical cities in the Yangtze River basin, including Jiujiang, Wuhu, Lu’an, Zhenjiang and Wuhan, this study investigated and summarized the characteristic variations and distribution differences of multiple indicators and substances from municipal sludge, dredged sludge, and river and lake sediments. The results demonstrated pH of multisource sludge was relatively stable in the neutral range. Organic matter and water content among municipal sludge were high and varied considerably between different wastewater treatment plants. Dredged sludge had an obviously higher sand content and wider particle distribution, which could be considered for graded utilization depending on its size. The nutrients composition of river and lake sediments was usually stable and special, with lower nitrogen and phosphorus content but higher potassium levels. The sources of heavy metals and persistent organic pollutants in multisource sludge were correlated, generally much higher among municipal sludge than dredged sludge and river and lake sediments, which were the most important limitation for final land utilization. Despite various properties of multisource sludge, the final fate and destination have some overall similarities, which need to be supplemented and improved by standards and laws. The study provided a preliminary analysis of suitable technical routes for municipal sludge, dredged sludge, river and lake sediments based on their different characteristics respectively, which was of great significance for multisource sludge co-treatment and disposal in the future of China.展开更多
The more diverse the ways and means of information acquisition are,the more complex and various the types of information are. The qualities of available information are usually uncertain,vague,imprecise,incomplete,and...The more diverse the ways and means of information acquisition are,the more complex and various the types of information are. The qualities of available information are usually uncertain,vague,imprecise,incomplete,and so on. However,the information is modeled and fused traditionally in particular,name some of the known theories: evidential,fuzzy sets,possibilistic,rough sets or conditional events,etc. For several years,researchers have explored the unification of theories enabling the fusion of multisource information and have finally considered random set theory as a powerful mathematical tool. This paper attempts to overall review the close relationships between random set theory and other theories,and introduce recent research results which present how different types of information can be dealt with in this unified framework. Finally,some possible future directions are discussed.展开更多
Background: The microneedle fractional RF handpiece used in our study (Intensif Handpiece, EndyMed Medical, Caesarea, Israel) is a novel handpiece that uses a tip with 25 non-insulated, gold plated microneedle electro...Background: The microneedle fractional RF handpiece used in our study (Intensif Handpiece, EndyMed Medical, Caesarea, Israel) is a novel handpiece that uses a tip with 25 non-insulated, gold plated microneedle electrodes. The needles are inserted into the skin by a specially designed electronically controlled, smooth motion motor minimizing patient discomfort. RF emission delivered over the whole dermal portion of the needle allows effective coagulation resulting in minimal or no bleeding, together with bulk volumetric heating. Study Design/Materials and Methods: The study included 20 patients, treated for depressed acne scars using the IntensifTM?Microneedles handpiece (EndyMed PRO Platform System, EndyMed Medical, Caesarea, Israel). The degree of clinical improvement was assessed by the global aesthetic improvement scale (GAIS) and subjects satisfaction by post treatment questionnaires. Results: The number of treatments per patient varied between 1 and 6 (average 3.3 treatments per patient). Eleven patients (55%) reported none to minimal pain, six (30%) moderate discomfort and only three (15%) reported significant pain. Objective evaluation of the improvement by a board certified dermatologist showed improvement in 95% of patients. 25% showed excellent improvement, 50% experienced good improvement, and the 20% showed minimal improvement. One patient showed no improvement. Conclusions: The presented results show that the tested electronically controlled motorized insertion, non-insulated microneedle treatment technology provides a minimal discomfort, minimal downtime, effective and safe treatment for depressed acne scars.展开更多
Development of drought monitoring techniques is important for understanding and mitigating droughts and for rational agricultural management. This study used data from multiple sources, including MOD13 A3, TRMM 3 B43,...Development of drought monitoring techniques is important for understanding and mitigating droughts and for rational agricultural management. This study used data from multiple sources, including MOD13 A3, TRMM 3 B43, and SRTMDEM, for Yunnan Province, China from 2009 to 2018 to calculate the tropical rainfall condition index(TRCI), vegetation condition index(VCI), temperature condition index(TCI), and elevation factors. Principal component analysis(PCA) and analytic hierarchy process(AHP) were used to construct comprehensive drought monitoring models for Yunnan Province. The reliability of the models was verified, following which the drought situation in Yunnan Province for the past ten years was analysed. The results showed that:(1) The comprehensive drought index(CDI) had a high correlation with the standardized precipitation index, standardized precipitation evapotranspiration index, temperature vegetation dryness index, and CLDAS(China Meteorological Administration land data assimilation system), indicating that the CDI was a strong indicator of drought through meteorological, remote sensing and soil moisture monitoring.(2) The droughts from 2009 to 2018 showed generally consistent spatiotemporal changes. Droughts occurred in most parts of the province, with an average drought frequency of 29% and four droughtprone centres.(3) Monthly drought coverage during 2009 to 2014 exceeded that over 2015 to 2018. January had the largest average drought coverage over the study period(61.92%). Droughts at most stations during the remaining months except for October exhibited a weakening trend(slope > 0). The CDI provides a novel approach for drought monitoring in areas with complex terrain such as Yunnan Province.展开更多
To analyze the effects of gas cannons on clouds and precipitation,multisource observational data,including those from National Centers for Environmental Prediction(NCEP)reanalysis,Hangzhou and Huzhou new-generation we...To analyze the effects of gas cannons on clouds and precipitation,multisource observational data,including those from National Centers for Environmental Prediction(NCEP)reanalysis,Hangzhou and Huzhou new-generation weather radars,laser disdrometer,ground-based automatic weather station,wind profiler radar,and Lin'an C-band dualpolarization radar,were adopted in this study.Based on the variational dual-Doppler wind retrieval method and the polarimetric variables obtained by the dual-polarization radar,we analyzed the microphysical processes and the variations in the macro-and microphysical quantities in clouds from the perspective of the synoptic background before precipitation enhancement,the polarization echo characteristics before,during and after enhancement,and the evolution of the fine three-dimensional kinematic structure and the microphysical structure.The results show that the precipitation enhancement operation promoted the development of radar echoes and prolonged their duration,and both the horizontal and vertical wind speeds increased.The dual-polarization radar echo showed that the diameter of the precipitation particles increased,and the concentration of raindrops increased after precipitation enhancement.The raindrops were lifted to a height corresponding to 0 to-20℃due to vertical updrafts.Based on the disdrometer data during precipitation enhancement,the concentration of small raindrops(lgN_(w))showed a significant increase,and the mass-weighted diameter D_(m)value decreased,indicating that the precipitation enhancement operation played a certain“lubricating”effect.After the precipitation enhancement,the concentration of raindrops did not change much compared with that during the enhancement process,while the Dm increased,corresponding to an increase in rain intensity.The results suggest the positive effect of gas cannons on precipitation enhancement.展开更多
Current exploration needs are satisfied by multisource technology,which offers low cost,high efficiency,and high precision.The delay time,which determines the separation effects of the multisource blended data,is one ...Current exploration needs are satisfied by multisource technology,which offers low cost,high efficiency,and high precision.The delay time,which determines the separation effects of the multisource blended data,is one of the most crucial parameters in the acquisition and separation of multisource data.This study uses the deblending method of multisource data based on a periodically varying cosine code and analyses the effects of the two parameters,namely,the period amplitude and period length,used in this method on the separation of the multisource blended data.Meanwhile,the obtained coherence data is used to prove the correlation between the separation of multisource data and the two parameters.Examples of synthetic and field data are adopted to demonstrate that from a qualitative perspective,increasing the amplitude of the periodic code improves the separation effect within a reasonable delay time range.When the period length varies in a suitable range,the secondary noise becomes relatively incoherent,resulting in the separation result with a higher signal-to-noise ratio(SNR).From a quantitative perspective,the significant values(Sig.)of the period amplitude and length on the SNRs are less than 0.05,verifying the correlation between the separation of multisource data and the two parameters.展开更多
Accurate displacement prediction is critical for the early warning of landslides.The complexity of the coupling relationship between multiple influencing factors and displacement makes the accurate prediction of displ...Accurate displacement prediction is critical for the early warning of landslides.The complexity of the coupling relationship between multiple influencing factors and displacement makes the accurate prediction of displacement difficult.Moreover,in engineering practice,insufficient monitoring data limit the performance of prediction models.To alleviate this problem,a displacement prediction method based on multisource domain transfer learning,which helps accurately predict data in the target domain through the knowledge of one or more source domains,is proposed.First,an optimized variational mode decomposition model based on the minimum sample entropy is used to decompose the cumulative displacement into the trend,periodic,and stochastic components.The trend component is predicted by an autoregressive model,and the periodic component is predicted by the long short-term memory.For the stochastic component,because it is affected by uncertainties,it is predicted by a combination of a Wasserstein generative adversarial network and multisource domain transfer learning for improved prediction accuracy.Considering a real mine slope as a case study,the proposed prediction method was validated.Therefore,this study provides new insights that can be applied to scenarios lacking sample data.展开更多
The existing multi-source contour matching studies have focused on the matching methods with consideration of topological relations and similarity measurement based on spatial Euclidean distance,while it is lack of ta...The existing multi-source contour matching studies have focused on the matching methods with consideration of topological relations and similarity measurement based on spatial Euclidean distance,while it is lack of taking the contour geometric features into account,which may lead to mismatching in map boundaries and areas with intensive contours or extreme terrain changes.In light of this,it is put forward that a matching strategy from coarse to precious based on the contour geometric features.The proposed matching strategy can be described as follows.Firstly,the point sequence is converted to feature sequence according to a feature descriptive function based on curvature and angle of normal vector.Then the level of similarity among multi-source contours is calculated by using the longest common subsequence solution.Accordingly,the identical contours could be matched based on the above calculated results.In the experiment for the proposed method,the reliability and efficiency of the matching method are verified using simulative datasets and real datasets respectively.It has been proved that the proposed contour matching strategy has a high matching precision and good applicability.展开更多
With the improvement of multisource information sensing and data acquisition capabilities inside tunnels,the availability of multimodal data in tunnel engineering has significantly increased.However,due to structural ...With the improvement of multisource information sensing and data acquisition capabilities inside tunnels,the availability of multimodal data in tunnel engineering has significantly increased.However,due to structural differences in multimodal data,traditional intelligent advanced geological prediction models have limited capacity for data fusion.Furthermore,the lack of pre-trained models makes it difficult for neural networks trained from scratch to deeply explore the features of multimodal data.To address these challenges,we utilize the fusion capability of knowledge graph for multimodal data and the pre-trained knowledge of large language models(LLMs)to establish an intelligent advanced geological prediction model(GeoPredict-LLM).First,we develop an advanced geological prediction ontology model,forming a knowledge graph database.Using knowledge graph embeddings,multisource and multimodal data are transformed into low-dimensional vectors with a unified structure.Secondly,pre-trained LLMs,through reprogramming,reconstruct these low-dimensional vectors,imparting linguistic characteristics to the data.This transformation effectively reframes the complex task of advanced geological prediction as a"language-based"problem,enabling the model to approach the task from a linguistic perspective.Moreover,we propose the prompt-as-prefix method,which enables output generation,while freezing the core of the LLM,thereby significantly reduces the number of training parameters.Finally,evaluations show that compared to neural network models without pre-trained models,GeoPredict-LLM significantly improves prediction accuracy.It is worth noting that as long as a knowledge graph database can be established,GeoPredict-LLM can be adapted to multimodal data mining tasks with minimal modifications.展开更多
The article mainly explores the Hopf bifurcation of a kind of nonlinear system with Gaussian white noise excitation and bounded random parameter.Firstly,the nonlinear system with multisource stochastic fac-tors is red...The article mainly explores the Hopf bifurcation of a kind of nonlinear system with Gaussian white noise excitation and bounded random parameter.Firstly,the nonlinear system with multisource stochastic fac-tors is reduced to an equivalent deterministic nonlinear system by the sequential orthogonal decomposi-tion method and the Karhunen-Loeve(K-L)decomposition theory.Secondly,the critical conditions about the Hopf bifurcation of the equivalent deterministic system are obtained.At the same time the influence of multisource stochastic factors on the Hopf bifurcation for the proposed system is explored.Finally,the theorical results are verified by the numerical simulations.展开更多
基金supported by the National Natural Science Foundation of China (grant numbers 42293351, and U2468221)。
文摘This paper addresses the accuracy and timeliness limitations of traditional comprehensive prediction methods by proposing an approach of decision-level fusion of multisource data.A risk prediction indicator system was established for water and mud inrush in tunnels by analyzing advanced prediction data for specifi c tunnel segments.Additionally,the indicator weights were determined using the analytic hierarchy process combined with the Huber weighting method.Subsequently,a multisource data decision-layer fusion algorithm was utilized to generate fused imaging results for tunnel water and mud inrush risk predictions.Meanwhile,risk analysis was performed for different tunnel sections to achieve spatial and temporal complementarity within the indicator system and optimize redundant information.Finally,model feasibility was validated using the CZ Project Sejila Mountain Tunnel segment as a case study,yielding favorable risk prediction results and enabling effi cient information fusion and support for construction decision-making.
基金supported by the Royal Golden Jubilee(RGJ)Ph.D.Programme(Grant No.PHD/0079/2561)through the National Research Council of Thailand(NRCT)and Thailand Research Fund(TRF).
文摘This research investigates the application of multisource data fusion using a Multi-Layer Perceptron (MLP) for Human Activity Recognition (HAR). The study integrates four distinct open-source datasets—WISDM, DaLiAc, MotionSense, and PAMAP2—to develop a generalized MLP model for classifying six human activities. Performance analysis of the fused model for each dataset reveals accuracy rates of 95.83 for WISDM, 97 for DaLiAc, 94.65 for MotionSense, and 98.54 for PAMAP2. A comparative evaluation was conducted between the fused MLP model and the individual dataset models, with the latter tested on separate validation sets. The results indicate that the MLP model, trained on the fused dataset, exhibits superior performance relative to the models trained on individual datasets. This finding suggests that multisource data fusion significantly enhances the generalization and accuracy of HAR systems. The improved performance underscores the potential of integrating diverse data sources to create more robust and comprehensive models for activity recognition.
基金Foundation of Key Laboratory of Smart Earth(KF2023ZD03-02)China Meteorological Administration Innovation development project(CXFZ2025J116)+1 种基金National Natural Science Foundation of China(42205197)Basic Research Fund of CAMS(2022Y023,2022Y025)。
文摘Video imagery enables both qualitative characterization and quantitative retrieval of low-visibility conditions.These phenomena exhibit complex nonlinear dependencies on atmospheric processes,particularly during moisture-driven weather events such as fog,rain,and snow.To address this challenge,we propose a dual-branch neural architecture that synergistically processes optical imagery and multi-source meteorological data(temperature,humidity,and wind speed).The framework employs a convolutional neural network(CNN)branch to extract visibility-related visual features from video imagery sequences,while a parallel artificial neural network(ANN)branch decodes nonlinear relationships among the meteorological factors.Cross-modal feature fusion is achieved through an adaptive weighting layer.To validate the framework,multimodal Backpropagation-VGG(BP-VGG)and Backpropagation-ResNet(BP-ResNet)models are developed and trained/tested using historical imagery and meteorological observations from Nanjing Lukou International Airport.The results demonstrate that the multimodal networks reduce retrieval errors by approximately 8%–10%compared to unimodal networks relying solely on imagery.Among the multimodal models,BP-ResNet exhibits the best performance with a mean absolute percentage error(MAPE)of 8.5%.Analysis of typical case studies reveals that visibility fluctuates rapidly while meteorological factors change gradually,highlighting the crucial role of high-frequency imaging data in intelligent visibility retrieval models.The superior performance of BP-ResNet over BP-VGG is attributed to its use of residual blocks,which enables BP-ResNet to excel in multimodal processing by effectively leveraging data complementarity for synergistic improvements.This study presents an end-to-end intelligent visibility inversion framework that directly retrieves visibility values,enhancing its applicability across industries.However,while this approach boosts accuracy and applicability,its performance in critical low-visibility scenarios remains suboptimal,necessitating further research into more advanced retrieval techniques—particularly under extreme visibility conditions.
基金Under the auspices of the Second Tibetan Plateau Scientific Expedition and Research Program(STEP,No.2019QZKK0608)。
文摘The construction of human settlements plays a vital role in achieving sustainable development goals.With the growing population,both urban and rural planning—as well as the development of human settlements—on the Qinghai-Tibet Plateau in China have received increasing attention.This study proposed a comprehensive framework to assess the quality of human settlements and identify their limiting factors of Nyingchi City,southeastern Qinghai-Tibet Plateau of China.The framework integrated a region-specific evaluation system tailored to the plateau’s unique characteristics and utilized multi-source data collected through field-based questionnaires and remote sensing.Analytical methods employed include the Criteria Importance Through Intercriteria Correlation(CRITIC)weighting method,difference analysis for evaluating spatial and categorical variations,and a novel approach introduced in this study for identifying limiting factors.In August 2021,a questionnaire-based survey was conducted in the southeastern Qinghai-Tibet Plateau,yielding 823 valid responses.The average evaluation score for human settlement quality(HSQ)was(6.96±0.94),indicating that settlement conditions were approaching the satisfaction threshold.Notably,the score for the health dimension was(6.28±1.41),reflecting relatively underdeveloped health services in the region.From the perspective of spatial patterns,despite its favorable natural conditions,the HSQ in Medog County was relatively backward,reflecting uncoordinated development that warrants attention.Significant differences were observed in the perceptions of human settlements among different groups in terms of ethnicity,income,and educational background.Low ratings for income and employment conditions represented a major limitation to the local HSQ.The development of human settlements in the southeastern Qinghai-Tibet Plateau still needs further promotion due to population disparities and the challenges of creating a healthy environment in high-altitude regions.The results are valuable for improving human settlements in plateau regions,which can help make targeted policy recommendations.
基金the“863”Marine Monitor of Hitech Research and Development Program of China under contract No.,5 2003AA604040 a, 2002AA639640.
文摘To meet the increasing demand of national spatial database infrastructure construction and application, a concept model of China's coastal zone scientific data platform is established based on the information feature analysis of a compound dataset, consisting of remote sensing data and conventional data. Based on this concept model, the detailed logical database structure and the storage strategy of remote sensing data and their metadata using ArcSDE are designed. The complicated technology of multisources data combination in this research is crucial to the future coastal zone and offshore database construction and practical running, which will provide intelligent information analysis and technological service for coastal zone and offshore investigation, research, development and management.
基金the support given by the government and official in Guangnan Countyfunded by[National Natural Science Foundation of China]grant number[41361020,40961031]+3 种基金[Joint Fund of Yunnan Provincial Science and Technology Department and Yunnan University]grant number[2018FY001(-017)][Project of Innovative Talents Cultivation for Graduate Students of Yunnan University]grant number[C176230200][Project of Internationalization and Cultural Inheritance and Innovation of Yunnan University]grant number[C176250202][Science Research Fund of Yunnan Provincial Education Department in 2020:Postgraduate]grant number[2020Y0030]。
文摘The karst mountainous area is an ecologically fragile region with prominent humanland contradictions.The resource-environment carrying capacity(RECC)of this region needs to be further clarified.The development of remote sensing(RS)and geographic information system(GIS)provides data sources and processing platform for RECC monitoring.This study analyzed and established the evaluation index system of RECC by considering particularity in the karst mountainous area of Southwest China;processed multisource RS data(Sentinel-2,Aster-DEM and Landsat-8)to extract the spatial distributions of nine key indexes by GIS techniques(information classification,overlay analysis and raster calculation);proposed the methods of index integration and fuzzy comprehensive evaluation of the RECC by GIS;and took a typical area,Guangnan County in Yunnan Province of China,as an experimental area to explore the effectiveness of the indexes and methods.The results showed that:(1)The important indexes affecting the RECC of karst mountainous area are water resources,tourism resources,position resources,geographical environment and soil erosion environment.(2)Data on cultivated land,construction land,minerals,transportation,water conservancy,ecosystem services,topography,soil erosion and rocky desertification can be obtained from RS data.GIS techniques integrate the information into the RECC results.The data extraction and processing methods are feasible on evaluating RECC.(3)The RECC of Guangnan County was in the mid-carrying level in 2018.The midcarrying and low-carrying levels were the main types,accounting for more than 80.00%of the total study area.The areas with high carrying capacity were mainly distributed in the northern regions of the northwest-southeast line of the county,and other areas have a low carrying capacity comparatively.The coordination between regional resource-environment status and socioeconomic development is the key to improve RECC.This study explores the evaluation index system of RECC in karst mountainous area and the application of multisource RS data and GIS techniques in the comprehensive evaluation.The methods can be applied in related fields to provide suggestions for data/information extraction and integration,and sustainable development.
基金supported by the National Natural Science Foundation of China(50979065,51109154 and 51249002)the Natural Science Foundation of Shanxi Province,China(2012021026-2)+2 种基金the Program for Science and Technology Development of Shanxi Province,China(20110311018-1)the Specialized Research Fund for the Doctoral Program of Higher Education,China(20111402120006,20121402110009)the Program for Graduate Student Education and Innovation of Shanxi Province,China(2015BY27)
文摘Crop root system plays an important role in the water cycle of the soil-plant-atmosphere continuum. In this study, com- bined isotope techniques, root length density and root cell activity analysis were used to investigate the root water uptake mechanisms of winter wheat （Triticum aesfivum L.） under different irrigation depths in the North China Plain. Both direct inference approach and multisource linear mixing model were applied to estimate the distribution of water uptake with depth in six growing stages. Results showed that winter wheat under land surface irrigation treatment （Ts） mainly absorbed water from 10-20 cm soil layers in the wintering and green stages （66.9 and 72.0%, respectively）; 0-20 cm （57.0%） in the jointing stage; 0-40 （15.3%） and 80-180 cm （58.1%） in the heading stage; 60-80 （13.2%） and 180-220 cm （35.5%） in the filling stage; and 0-40 （46.8%） and 80-100 cm （31.0%） in the ripening stage. Winter wheat under whole soil layers irrigation treatment （Tw） absorbed more water from deep soil layer than Ts in heading, filling and ripening stages. Moreover, root cell activity and root length density of winter wheat under TW were significantly greater than that of Ts in the three stages. We concluded that distribution of water uptake with depth was affected by the availability of water sources, the root length density and root cell activity. Implementation of the whole soil layers irrigation method can affect root system distribution and thereby increase water use from deeper soil and enhance water use efficiency.
基金supported by the National Natural Science Foundation of China(Nos.31500518,31500519,and 31470640)
文摘We developed a forest type classification technology for the Daxing＇an Mountains of northeast China using multisource remote sensing data.A SPOT-5 image and two temporal images of RADARSAT-2 full-polarization SAR were used to identify forest types in the Pangu Forest Farm of the Daxing＇an Mountains.Forest types were identified using random forest（RF） classification with the following data combination types： SPOT-5 alone,SPOT-5 and SAR images in August or November,and SPOT-5 and two temporal SAR images.We identified many forest types using a combination of multitemporal SAR and SPOT-5 images,including Betula platyphylla,Larix gmelinii,Pinus sylvestris and Picea koraiensis forests.The accuracy of classification exceeded 88% and improved by 12% when compared to the classification results obtained using SPOT data alone.RF classification using a combination of multisource remote sensing data improved classification accuracy compared to that achieved using single-source remote sensing data.
基金supported by the Sichuan Meteorological Bureau,the Sichuan Meteorological Observation and Data Centerthe Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province[grant number SCQXKJQN202121]+1 种基金the Key Technology Development Project of Weather Forecasting[grant number YBGJXM(2020)1A-08]the Innovative Development Project of the China Meteorological Administration[grant number CXFZ2021Z007]。
文摘High-quality and high-resolution precipitation data are the basis for mesoscale numerical weather forecasting,model verification,and hydrological monitoring,which play an important role in meteorological and hydrological disaster prevention and mitigation.In this study,high-density rain gauge data are used to evaluate the fusion accuracy of the China Meteorological Administration Multisource Precipitation Analysis System(CMPAS),and four CMPAS products with different spatial and temporal resolution and different data sources are compared,to derive the applicability of CMPAS.Results show that all the CMPAS products show high accuracy in the Sichuan Basin,followed by Panxi Area and the western Sichuan Plateau.The errors of the four products all rise with the increase in precipitation.CMPAS overestimates precipitation in summer and autumn and underestimates it in spring and winter.Overall,the applicability of these fused data in the Sichuan Basin is quite good.Due to the lack of observations and the influence of the terrain and meteorological conditions,the evaluation of CMPAS in the plateau area needs further analysis.
基金This work was supported by the National Natural Science Foundation of China(No.62022061)Tianjin Natural Science Foundation(No.20JCYBJC00880)Beijing Key Laboratory Open Fund of Long-Life Technology of Precise Rotation and Transmission Mechanisms.
文摘Single gimbal control moment gyroscope(SGCMG)with high precision and fast response is an important attitude control system for high precision docking,rapid maneuvering navigation and guidance system in the aerospace field.In this paper,considering the influence of multi-source disturbance,a data-based feedback relearning(FR)algorithm is designed for the robust control of SGCMG gimbal servo system.Based on adaptive dynamic programming and least-square principle,the FR algorithm is used to obtain the servo control strategy by collecting the online operation data of SGCMG system.This is a model-free learning strategy in which no prior knowledge of the SGCMG model is required.Then,combining the reinforcement learning mechanism,the servo control strategy is interacted with system dynamic of SGCMG.The adaptive evaluation and improvement of servo control strategy against the multi-source disturbance are realized.Meanwhile,a data redistribution method based on experience replay is designed to reduce data correlation to improve algorithm stability and data utilization efficiency.Finally,by comparing with other methods on the simulation model of SGCMG,the effectiveness of the proposed servo control strategy is verified.
基金supported by the Scientific Research Project of China Three Gorges Corporation, China (No. 202003081)the National Key Research and Development Program of China (No. 2020YFC1908702)the National Natural Science Foundation of China (NSFC) (No. 52131002)。
文摘Sludge is the by-product of wastewater treatment process. Multisource sludge can be defined as sludge from different sources. Based on the sludge properties of five typical cities in the Yangtze River basin, including Jiujiang, Wuhu, Lu’an, Zhenjiang and Wuhan, this study investigated and summarized the characteristic variations and distribution differences of multiple indicators and substances from municipal sludge, dredged sludge, and river and lake sediments. The results demonstrated pH of multisource sludge was relatively stable in the neutral range. Organic matter and water content among municipal sludge were high and varied considerably between different wastewater treatment plants. Dredged sludge had an obviously higher sand content and wider particle distribution, which could be considered for graded utilization depending on its size. The nutrients composition of river and lake sediments was usually stable and special, with lower nitrogen and phosphorus content but higher potassium levels. The sources of heavy metals and persistent organic pollutants in multisource sludge were correlated, generally much higher among municipal sludge than dredged sludge and river and lake sediments, which were the most important limitation for final land utilization. Despite various properties of multisource sludge, the final fate and destination have some overall similarities, which need to be supplemented and improved by standards and laws. The study provided a preliminary analysis of suitable technical routes for municipal sludge, dredged sludge, river and lake sediments based on their different characteristics respectively, which was of great significance for multisource sludge co-treatment and disposal in the future of China.
基金Supported in part by the NSFC (No.60934009,60874105)the ZJNSF (Y1080422, R106745)NCET (08-0345)
文摘The more diverse the ways and means of information acquisition are,the more complex and various the types of information are. The qualities of available information are usually uncertain,vague,imprecise,incomplete,and so on. However,the information is modeled and fused traditionally in particular,name some of the known theories: evidential,fuzzy sets,possibilistic,rough sets or conditional events,etc. For several years,researchers have explored the unification of theories enabling the fusion of multisource information and have finally considered random set theory as a powerful mathematical tool. This paper attempts to overall review the close relationships between random set theory and other theories,and introduce recent research results which present how different types of information can be dealt with in this unified framework. Finally,some possible future directions are discussed.
文摘Background: The microneedle fractional RF handpiece used in our study (Intensif Handpiece, EndyMed Medical, Caesarea, Israel) is a novel handpiece that uses a tip with 25 non-insulated, gold plated microneedle electrodes. The needles are inserted into the skin by a specially designed electronically controlled, smooth motion motor minimizing patient discomfort. RF emission delivered over the whole dermal portion of the needle allows effective coagulation resulting in minimal or no bleeding, together with bulk volumetric heating. Study Design/Materials and Methods: The study included 20 patients, treated for depressed acne scars using the IntensifTM?Microneedles handpiece (EndyMed PRO Platform System, EndyMed Medical, Caesarea, Israel). The degree of clinical improvement was assessed by the global aesthetic improvement scale (GAIS) and subjects satisfaction by post treatment questionnaires. Results: The number of treatments per patient varied between 1 and 6 (average 3.3 treatments per patient). Eleven patients (55%) reported none to minimal pain, six (30%) moderate discomfort and only three (15%) reported significant pain. Objective evaluation of the improvement by a board certified dermatologist showed improvement in 95% of patients. 25% showed excellent improvement, 50% experienced good improvement, and the 20% showed minimal improvement. One patient showed no improvement. Conclusions: The presented results show that the tested electronically controlled motorized insertion, non-insulated microneedle treatment technology provides a minimal discomfort, minimal downtime, effective and safe treatment for depressed acne scars.
基金This research was funded by the Multigovernment International Science and Technology Innovation Cooperation Key Project of the National Key Research and Development Program of China(Grant No.2018YFE0184300)Erasmus+Capacity Building in Higher Education of the Education,Audiovisual and Culture Executive Agency(EACEA)(Grant No.586037-EPP-1-2017-1-HU-EPPKA2CBHE-JP)+3 种基金the National Natural Science Foundation of China(Grant No.41561048)the Technical Methods and Empirical Study on Ecological Assets Measurement in County Level of Yunnan Province(Grant No.ZDZZD201506)the Young and Middleaged Academic and Technical Leaders Reserve Talents Training Program of Yunnan Province(Grant No.2008PY056)the Program for Innovative Research Team(in Science and Technology)at the University of Yunnan Province,IRTSTYN。
文摘Development of drought monitoring techniques is important for understanding and mitigating droughts and for rational agricultural management. This study used data from multiple sources, including MOD13 A3, TRMM 3 B43, and SRTMDEM, for Yunnan Province, China from 2009 to 2018 to calculate the tropical rainfall condition index(TRCI), vegetation condition index(VCI), temperature condition index(TCI), and elevation factors. Principal component analysis(PCA) and analytic hierarchy process(AHP) were used to construct comprehensive drought monitoring models for Yunnan Province. The reliability of the models was verified, following which the drought situation in Yunnan Province for the past ten years was analysed. The results showed that:(1) The comprehensive drought index(CDI) had a high correlation with the standardized precipitation index, standardized precipitation evapotranspiration index, temperature vegetation dryness index, and CLDAS(China Meteorological Administration land data assimilation system), indicating that the CDI was a strong indicator of drought through meteorological, remote sensing and soil moisture monitoring.(2) The droughts from 2009 to 2018 showed generally consistent spatiotemporal changes. Droughts occurred in most parts of the province, with an average drought frequency of 29% and four droughtprone centres.(3) Monthly drought coverage during 2009 to 2014 exceeded that over 2015 to 2018. January had the largest average drought coverage over the study period(61.92%). Droughts at most stations during the remaining months except for October exhibited a weakening trend(slope > 0). The CDI provides a novel approach for drought monitoring in areas with complex terrain such as Yunnan Province.
基金National Natural Science Foundation of China(41675029)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX18_0998)+1 种基金Science and Technology Program of Huzhou(2021GZ14,2020GZ31)Science and Technology(Key)Program of Zhejiang Meteorological Service(2021ZD27)。
文摘To analyze the effects of gas cannons on clouds and precipitation,multisource observational data,including those from National Centers for Environmental Prediction(NCEP)reanalysis,Hangzhou and Huzhou new-generation weather radars,laser disdrometer,ground-based automatic weather station,wind profiler radar,and Lin'an C-band dualpolarization radar,were adopted in this study.Based on the variational dual-Doppler wind retrieval method and the polarimetric variables obtained by the dual-polarization radar,we analyzed the microphysical processes and the variations in the macro-and microphysical quantities in clouds from the perspective of the synoptic background before precipitation enhancement,the polarization echo characteristics before,during and after enhancement,and the evolution of the fine three-dimensional kinematic structure and the microphysical structure.The results show that the precipitation enhancement operation promoted the development of radar echoes and prolonged their duration,and both the horizontal and vertical wind speeds increased.The dual-polarization radar echo showed that the diameter of the precipitation particles increased,and the concentration of raindrops increased after precipitation enhancement.The raindrops were lifted to a height corresponding to 0 to-20℃due to vertical updrafts.Based on the disdrometer data during precipitation enhancement,the concentration of small raindrops(lgN_(w))showed a significant increase,and the mass-weighted diameter D_(m)value decreased,indicating that the precipitation enhancement operation played a certain“lubricating”effect.After the precipitation enhancement,the concentration of raindrops did not change much compared with that during the enhancement process,while the Dm increased,corresponding to an increase in rain intensity.The results suggest the positive effect of gas cannons on precipitation enhancement.
基金supported by the National Key Research and Development Program of China(2018YFA0702503)the National Natural Science Foundation of China(41674122).
文摘Current exploration needs are satisfied by multisource technology,which offers low cost,high efficiency,and high precision.The delay time,which determines the separation effects of the multisource blended data,is one of the most crucial parameters in the acquisition and separation of multisource data.This study uses the deblending method of multisource data based on a periodically varying cosine code and analyses the effects of the two parameters,namely,the period amplitude and period length,used in this method on the separation of the multisource blended data.Meanwhile,the obtained coherence data is used to prove the correlation between the separation of multisource data and the two parameters.Examples of synthetic and field data are adopted to demonstrate that from a qualitative perspective,increasing the amplitude of the periodic code improves the separation effect within a reasonable delay time range.When the period length varies in a suitable range,the secondary noise becomes relatively incoherent,resulting in the separation result with a higher signal-to-noise ratio(SNR).From a quantitative perspective,the significant values(Sig.)of the period amplitude and length on the SNRs are less than 0.05,verifying the correlation between the separation of multisource data and the two parameters.
基金supported by the National Natural Science Foundation of China(Grant No.51674169)Department of Education of Hebei Province of China(Grant No.ZD2019140)+1 种基金Natural Science Foundation of Hebei Province of China(Grant No.F2019210243)S&T Program of Hebei(Grant No.22375413D)School of Electrical and Electronics Engineering。
文摘Accurate displacement prediction is critical for the early warning of landslides.The complexity of the coupling relationship between multiple influencing factors and displacement makes the accurate prediction of displacement difficult.Moreover,in engineering practice,insufficient monitoring data limit the performance of prediction models.To alleviate this problem,a displacement prediction method based on multisource domain transfer learning,which helps accurately predict data in the target domain through the knowledge of one or more source domains,is proposed.First,an optimized variational mode decomposition model based on the minimum sample entropy is used to decompose the cumulative displacement into the trend,periodic,and stochastic components.The trend component is predicted by an autoregressive model,and the periodic component is predicted by the long short-term memory.For the stochastic component,because it is affected by uncertainties,it is predicted by a combination of a Wasserstein generative adversarial network and multisource domain transfer learning for improved prediction accuracy.Considering a real mine slope as a case study,the proposed prediction method was validated.Therefore,this study provides new insights that can be applied to scenarios lacking sample data.
基金National Science Foundation of China(Nos.41801388,41901397)。
文摘The existing multi-source contour matching studies have focused on the matching methods with consideration of topological relations and similarity measurement based on spatial Euclidean distance,while it is lack of taking the contour geometric features into account,which may lead to mismatching in map boundaries and areas with intensive contours or extreme terrain changes.In light of this,it is put forward that a matching strategy from coarse to precious based on the contour geometric features.The proposed matching strategy can be described as follows.Firstly,the point sequence is converted to feature sequence according to a feature descriptive function based on curvature and angle of normal vector.Then the level of similarity among multi-source contours is calculated by using the longest common subsequence solution.Accordingly,the identical contours could be matched based on the above calculated results.In the experiment for the proposed method,the reliability and efficiency of the matching method are verified using simulative datasets and real datasets respectively.It has been proved that the proposed contour matching strategy has a high matching precision and good applicability.
基金the National Natural Science Foundation of China(Grant Nos.52279103 and 52379103)。
文摘With the improvement of multisource information sensing and data acquisition capabilities inside tunnels,the availability of multimodal data in tunnel engineering has significantly increased.However,due to structural differences in multimodal data,traditional intelligent advanced geological prediction models have limited capacity for data fusion.Furthermore,the lack of pre-trained models makes it difficult for neural networks trained from scratch to deeply explore the features of multimodal data.To address these challenges,we utilize the fusion capability of knowledge graph for multimodal data and the pre-trained knowledge of large language models(LLMs)to establish an intelligent advanced geological prediction model(GeoPredict-LLM).First,we develop an advanced geological prediction ontology model,forming a knowledge graph database.Using knowledge graph embeddings,multisource and multimodal data are transformed into low-dimensional vectors with a unified structure.Secondly,pre-trained LLMs,through reprogramming,reconstruct these low-dimensional vectors,imparting linguistic characteristics to the data.This transformation effectively reframes the complex task of advanced geological prediction as a"language-based"problem,enabling the model to approach the task from a linguistic perspective.Moreover,we propose the prompt-as-prefix method,which enables output generation,while freezing the core of the LLM,thereby significantly reduces the number of training parameters.Finally,evaluations show that compared to neural network models without pre-trained models,GeoPredict-LLM significantly improves prediction accuracy.It is worth noting that as long as a knowledge graph database can be established,GeoPredict-LLM can be adapted to multimodal data mining tasks with minimal modifications.
基金This work was supported by the grants from the National Nat-ural Science Foundation of China(No.11772002)Ningxia higher education first-class discipline construction funding project(No.NXYLXK2017B09)+2 种基金Major Special project of North Minzu University(No.ZDZX201902)Open project of The Key Laboratory of In-telligent Information and Big Data Processing of NingXia Province(No.2019KLBD008)Postgraduate Innovation Project of North Minzu University(No.YCX22099).
文摘The article mainly explores the Hopf bifurcation of a kind of nonlinear system with Gaussian white noise excitation and bounded random parameter.Firstly,the nonlinear system with multisource stochastic fac-tors is reduced to an equivalent deterministic nonlinear system by the sequential orthogonal decomposi-tion method and the Karhunen-Loeve(K-L)decomposition theory.Secondly,the critical conditions about the Hopf bifurcation of the equivalent deterministic system are obtained.At the same time the influence of multisource stochastic factors on the Hopf bifurcation for the proposed system is explored.Finally,the theorical results are verified by the numerical simulations.
