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Risk Prediction of Tunnel Water and Mud Inrush Based on Decision-Level Fusion of Multisource Data
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作者 Shi-shu Zhang Peng Wang +4 位作者 Hua-bo Xiao Huai-bing Wang Yi-guo Xue Wei-dong Chen Kai Zhang 《Applied Geophysics》 2025年第2期472-487,559,560,共18页
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
关键词 Tunnel water and mud inrush prediction methods risk indicators multisource data decision-level fusion
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Validation of Urban Surface Water Flood Modeling with Multisource Data:Two Case Studies in Baoji and Linyi Cities,China
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作者 Guizhen Guo Jie Yin +4 位作者 Xuesong Yuan Ziqing Zhu Mingfu Guan Dapeng Yu Nigel Wright 《International Journal of Disaster Risk Science》 2025年第5期832-842,共11页
Urban areas are particularly vulnerable to surface water flooding in a changing environment.A large number of urban surface water flood models have been developed to derive flood inundations and support risk managemen... Urban areas are particularly vulnerable to surface water flooding in a changing environment.A large number of urban surface water flood models have been developed to derive flood inundations and support risk management.However,unlike fluvial and coastal flooding,urban pluvial flooding is often associated with shallow water and thus the model is difficult to validate with traditional monitoring data.In this study,we first developed a full two-dimensional(2D)hydrodynamic model for simulating surface water floods.We further evaluated the model performance with multisource data from flood incidents,including official reports and social media data.The model was tested in the cities of Baoji and Linyi,China,where two surface water flood events recently occurred and caused considerable losses and casualties.In total,350 localized flooding incidents were obtained for the two cities(220 in Baoji and 130 in Linyi)and 313 reports were retained after data cleaning(202 in Baoji and 111 in Linyi).Over 90%of the reported flood incidents fall in urban areas where water depths are predicted to be higher than 0.15 m.The results demonstrate that the model is able to derive the broad patterns of flood inundation at the city scale.The approach tested here could be applied to other flood-prone cities and future research could include water depth information for more robust model validation. 展开更多
关键词 Model validation multisource data Surface water fl ooding Urban fl ood modeling
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Multisource Data Fusion Using MLP for Human Activity Recognition
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作者 Sujittra Sarakon Wansuree Massagram Kreangsak Tamee 《Computers, Materials & Continua》 2025年第2期2109-2136,共28页
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
关键词 multisource data fusion human activity recognition multi-layer perceptron(MLP) artificial intelligent
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Slope displacement prediction based on multisource domain transfer learning for insufficient sample data 被引量:1
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作者 Zheng Hai-Qing Hu Lin-Ni +2 位作者 Sun Xiao-Yun Zhang Yu Jin Shen-Yi 《Applied Geophysics》 SCIE CSCD 2024年第3期496-504,618,共10页
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
关键词 slope displacement multisource domain transfer learning(MDTL) variational mode decomposition(VMD) generative adversarial network(GAN) Wasserstein-GAN
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China’s poverty assessment and analysis under the framework of the UN SDGs based on multisource remote sensing data
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作者 Mengjie Wang Yanjun Wang +3 位作者 Fei Teng Shaochun Li Yunhao Lin Hengfan Cai 《Geo-Spatial Information Science》 CSCD 2024年第1期111-131,共21页
Poverty has always been a global concern that has restricted human development.The first goal(SDG 1)of the United Nations Sustainable Development Goals(SDGs)is to eliminate all forms of poverty all over the world.The ... Poverty has always been a global concern that has restricted human development.The first goal(SDG 1)of the United Nations Sustainable Development Goals(SDGs)is to eliminate all forms of poverty all over the world.The establishment of a scientific and effective localized SDG 1 evaluation and monitoring method is the key to achieving SDG 1.This paper proposes SDG 1 China district and county-level localization evaluation method based on multi-source remote sensing data for the United Nations Sustainable Development Framework.The temporal and spatial distribution characteristics of China’s poverty areas and their SDG 1 evaluation values in 2012,2014,2016,and 2018 have been analyzed.Based on the SDGs global indicator framework,this paper first constructed SDG 1 China’s district and county localization indicator system and then extracted multidimensional feature factors from nighttime light images,land cover data,and digital elevation model data.Secondly,we establish SDG 1 China’s localized partial least squares estimation model and SDG 1 China’s localized machine learning estimation model.Finally,we analyze and verify the spatiotemporal distribution characteristics of China’s poverty areas and counties and their SDG 1 evaluation values.The results show that SDG 1 China’s district and county localization indicator system proposed in this study and SDG 1 China’s localized partial least squares estimation model can better reflect the poverty level of China’s districts and counties.The estimated model R^(2) is 0.65,which can identify 72.77%of China’s national poverty counties.From 2012 to 2018,the spatial distribution pattern of SDG evaluation values in China’s districts and counties is that the SDG evaluation values gradually increase from western China to eastern China.In addition,the average SDG 1 evaluation value of China’s districts and counties increased by 23%from 2012 to 2018.This paper is oriented to the United Nations SDGs framework,explores the SDG 1 localized evaluation method of China’s districts and counties based on multisource remote sensing data,and provides a scientific and rapid regional poverty monitoring and evaluation program for the implementation of the 2030 agenda poverty alleviation goals. 展开更多
关键词 multisource remote sensing data Sustainable Development Goals(SDGs) poverty indicator system partial least squares machine learning
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Impact of human settlements quality on urban vitality based on multisource data:A case study of Shahekou District,Dalian,China
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作者 LIU He 《Ecological Economy》 2024年第2期139-159,共21页
Urban geography has always been concerned about the influence of human settlements on urban vitality,but few studies reveal the influence of human settlements on urban vitality at a micro-scale.This paper analyzes the... Urban geography has always been concerned about the influence of human settlements on urban vitality,but few studies reveal the influence of human settlements on urban vitality at a micro-scale.This paper analyzes the spatial distribution characteristics of human settlements’quality and urban vitality at the micro-scale using Geodetectors and geographic weighted regression to analyze the relationship between human settlements and urban vitality.The results are shown as follows:there is still a significant development space for human settlements quality in Shahekou District,with obvious spatial dependence characteristics and significant gaps between various systems;the urban vitality of Shahekou District has obvious timeliness,and the urban vitality undergoes significant changes over time,which is related to the human settlements quality.The spatial distribution presents a single core spatial distribution structure with strong relative stability.The spatial distribution of cold and hot spots shows a pattern of“high in the north and low in the south,high in the east and low in the west”,with an increasing trend from southwest to northeast;the reachability of public transport has a significant impact on urban vitality.Its synergy with other variables is the leading force forming the spatial distribution of urban vitality.The environmental system,support system and social system are the significant factors affecting the urban vitality of Shahekou District. 展开更多
关键词 human settlements urban vitality refined management multisource data
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Construction and implementation of multisource spatial data management system of China's coastal zone and offshore 被引量:3
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作者 DUYunyan WANGJinggui +1 位作者 WANGZuoyong YANGXiaomei 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2004年第1期97-108,共12页
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
关键词 China's coastal zone multisources data concept models information system technological platform
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Integrating multisource RS data and GIS techniques to assist the evaluation of resource-environment carrying capacity in karst mountainous area 被引量:9
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作者 PU Jun-wei ZHAO Xiao-qing +4 位作者 MIAO Pei-pei LI Si-nan TAN Kun WANG Qian TANG Wei 《Journal of Mountain Science》 SCIE CSCD 2020年第10期2528-2547,共20页
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
关键词 Carrying capacity multisource RS data GIS techniques Evaluation index system Data Integration Karst mountainous area Fuzzy comprehensive evaluation method
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RANDOM SETS: A UNIFIED FRAMEWORK FOR MULTISOURCE INFORMATION FUSION 被引量:3
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作者 Xu Xiaobin Wen Chenglin 《Journal of Electronics(China)》 2009年第6期723-730,共8页
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
关键词 multisource information fusion Random set theory Imperfect information
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Effects of periodically varying codes on separation of multisource blended data 被引量:1
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作者 Jiao Meng-Yao Hu Tian-Yue +4 位作者 Liu Yang Yu Zhen-Zhen Liang Shang-Lin Liu Li-Chao Ji-Wei 《Applied Geophysics》 SCIE CSCD 2021年第3期331-344,432,共15页
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
关键词 multisource technology periodically varying cosine code period amplitude period length correlation
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Insights into multisource sludge distributed in the Yangtze River basin, China: Characteristics,correlation, treatment and disposal 被引量:1
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作者 Yiqun Guo Hui Gong +7 位作者 Wenjing Shi Ning Fang Yaqin Tan Weiqi Zhou Jialiang Huang Lingling Dai Xiaohu Dai Yali Guo 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2023年第4期321-332,共12页
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
关键词 multisource sludge Basic characteristics Potential correlation Treatment and disposal Heavy metals Persistent organic pollutants
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A Multisource Contour Matching Method Considering the Similarity of Geometric Features 被引量:8
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作者 Wenyue GUO Anzhu YU +4 位作者 Qun SUN Shaomei LI Qing XU Bowei WEN Yuanfu LI 《Journal of Geodesy and Geoinformation Science》 2020年第3期76-87,共12页
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
关键词 multisource contour matching geometric feature similarity measurement longest common subsequence feature descriptor
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Comprehensive drought monitoring in Yunnan Province, China using multisource remote sensing data 被引量:1
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作者 WANG Jin-liang YU Yuan-he 《Journal of Mountain Science》 SCIE CSCD 2021年第6期1537-1549,共13页
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
关键词 multisource data Comprehensive drought index(CDI) Standardized precipitation index(SPI) Standardized precipitation evapotranspiration index(SPEI) Temperature vegetation dryness index(TVDI) Yunnan Province China
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Hopf bifurcation of nonlinear system with multisource stochastic factors
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作者 Xinyu Bai Shaojuan Ma +1 位作者 Qianling Zhang Qiyi Liu 《Theoretical & Applied Mechanics Letters》 CAS CSCD 2023年第2期93-97,共5页
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
关键词 multisource stochastic factors Gaussian white noise K-L decomposition Hopf bifurcation Random parameter
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基于多源遥感NDVI时序曲线特征的田区尺度冬小麦物候期提取 被引量:2
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作者 张晓春 况梦柯 +2 位作者 史良胜 钟立傲 易鸣 《农业工程学报》 北大核心 2025年第1期181-191,共11页
冬小麦是中国北方地区主要的粮食作物。物候是随季节变化的特定生命周期事件,准确获取区域冬小麦物候期对指导粮食作物生产具有重要意义。传统的物候期监测方法主要基于野外实地观测,在时间和空间范围上存在局限性。遥感技术的发展使得... 冬小麦是中国北方地区主要的粮食作物。物候是随季节变化的特定生命周期事件,准确获取区域冬小麦物候期对指导粮食作物生产具有重要意义。传统的物候期监测方法主要基于野外实地观测,在时间和空间范围上存在局限性。遥感技术的发展使得长时间、大范围的冬小麦物候监测成为可能。目前遥感物候监测结果是以像元为单位空间分辨率较低的栅格影像,而以田区地块为单元的物候期图更符合实际作物生长状况。为了提高物候期分布图的空间分辨率和精度,并获取田区尺度冬小麦物候期图,该研究首先基于多源高时空分辨率遥感数据建立时间上非均匀的NDVI影像数据集(2017年9月—2023年7月),然后基于插值法获取均匀的每日NDVI数据集,并通过SG滤波重构获取能够反映冬小麦真实生长状态的NDVI时序曲线。最后基于冬小麦NDVI时序曲线特征与物候特征对应关系,采用极值法和动态阈值法提取了生长季开始期(播种)、峰值期(抽穗)、成熟期和结束期4种物候期的栅格影像,并将像元尺度的物候期结果转为田区尺度。结果显示:2017—2018年度冬小麦播种期晚于其他5年;2019—2020年度和2020—2021年度抽穗期明显早于其他4年;2019—2020年度冬小麦成熟时间早于其他5年,同时该年度生长季结束期也早于其他5年。通过验证对比发现遥感物候期结果与田间数据和其他物候研究结果一致,满足物候期县域田区尺度提取的需求。进一步讨论冬小麦遥感抽穗期结果与气候变化响应,发现抽穗期与当年气温、降水量和日照时数关系密切。研究综合运用高分一号、环境二号、Landsat-8和哨兵二号多源光学遥感影像,准确提取了6年冬小麦田区尺度物候期的空间分布图,可为监测冬小麦生长发育状态提供科学依据。 展开更多
关键词 归一化植被指数 遥感 物候期 冬小麦 多源遥感影像 田区尺度
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基于“空天地”同步测量的卫星遥感影像大气校正实验方案设计
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作者 崔建勇 张旺辰 +3 位作者 侯舒航 任鹏 刘善伟 宿新元 《实验技术与管理》 北大核心 2025年第6期9-19,共11页
针对卫星遥感影像大气校正精度受限的问题,提出一种基于无人机高光谱协同的“空天地”逐级校正方案。该研究以青岛市唐岛湾水域为实验区,结合卫星、高光谱无人机及地面光谱仪同步观测数据,设计多平台协同校正方案。首先通过逐像素匹配法... 针对卫星遥感影像大气校正精度受限的问题,提出一种基于无人机高光谱协同的“空天地”逐级校正方案。该研究以青岛市唐岛湾水域为实验区,结合卫星、高光谱无人机及地面光谱仪同步观测数据,设计多平台协同校正方案。首先通过逐像素匹配法(MPP)与经验线法(ELM)融合消除低空大气干扰;再利用指数三角优化算法(ETO)改进BP神经网络,建立卫星与无人机数据的非线性映射关系。实验结果显示,“空天地”逐级校正后卫星影像地表反射率与实测光谱的决定系数(R^(2))达0.92;叶绿素a(Chl-a)反演均方根误差(RMSE)降低至1.21μg/L,反演精度较校正前提升42%。研究表明,该实验方案可以有效提高卫星影像的大气校正精度。 展开更多
关键词 大气校正 多源数据 水色遥感 高光谱 BP神经网络
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地下煤火区遥感探测识别方法研究综述
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作者 陈宇 程惠斌 +4 位作者 杜培军 魏军 郎丰铠 丁凯文 索之辉 《遥感技术与应用》 北大核心 2025年第4期816-834,共19页
地下煤火被称为“没有地理界限”的全球性灾难,不仅造成了煤炭资源的巨大浪费,还对生态环境和社会安全发展构成了严重威胁。遥感技术在探测识别地下煤火的长期应用中展现出了独特优势,为煤火的监测和治理提供了重要的技术支撑。围绕地... 地下煤火被称为“没有地理界限”的全球性灾难,不仅造成了煤炭资源的巨大浪费,还对生态环境和社会安全发展构成了严重威胁。遥感技术在探测识别地下煤火的长期应用中展现出了独特优势,为煤火的监测和治理提供了重要的技术支撑。围绕地下煤火引发的典型地表响应特征,阐述了煤火区遥感探测识别的基本原理,对现有地下煤火区遥感探测识别方法进行了系统分析和综述,并探讨了各个方法的优势和局限性。在此基础上,剖析了当前研究存在的不足,并对面临的挑战和未来的发展方向进行了展望。 展开更多
关键词 地下煤火 探测识别 热异常 地表形变 多源遥感 多特征耦合
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粉煤灰混凝土氯离子扩散系数的广源大样本模型 被引量:1
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作者 杨绿峰 朱恩 《材料导报》 北大核心 2025年第21期109-115,共7页
为了克服现有的粉煤灰混凝土氯离子扩散系数模型不能反映水泥和粉煤灰等胶凝材料品质的影响、预测精度低的问题,基于广源大样本RCM试验数据,利用两相回归法建立了考虑水泥品类和粉煤灰等级影响的氯离子扩散系数高精度计算模型。首先,基... 为了克服现有的粉煤灰混凝土氯离子扩散系数模型不能反映水泥和粉煤灰等胶凝材料品质的影响、预测精度低的问题,基于广源大样本RCM试验数据,利用两相回归法建立了考虑水泥品类和粉煤灰等级影响的氯离子扩散系数高精度计算模型。首先,基于粉煤灰混凝土RCM试验的广源大样本数据,通过回归分析确定水胶比的线性函数和粉煤灰掺量的二次函数适合于建立氯离子扩散系数模型。其次,利用两相回归法确定水泥品类因子和粉煤灰品质因子对应于不同水泥品类、不同粉煤灰等级的取值,据此建立考虑粉煤灰等级、水泥类型及其强度等级影响的混凝土氯离子扩散系数预测模型。对比分析结果表明,广源大样本模型在一定程度上提升了粉煤灰混凝土氯离子扩散系数的预测精度和稳定性。但当不考虑胶凝材料品质影响时,模型预测精度和稳定性的提升效果有时不明显。本文模型通过引入水泥品类因子和粉煤灰品质因子考虑胶凝材料品质影响,能够进一步使加权平均误差降低41.7%、使变异系数降低34.3%,从而大幅提升氯离子扩散系数的预测精度和适应性。 展开更多
关键词 粉煤灰混凝土 粉煤灰品质因子 水泥品类因子 氯离子扩散系数 快速电子迁移(RCM) 广源大样本
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技术突破和场景牵引视角下颠覆性技术量化识别方法研究
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作者 王燕鹏 王学昭 《情报理论与实践》 北大核心 2025年第3期143-150,159,共9页
[目的/意义]立足国家战略需求,构建透明化、规范化、可循证的颠覆性技术量化识别方法。[方法/过程]从颠覆性技术的技术突破和场景牵引来源出发,综合采用科技战略动态、科技前沿动态、权威预测清单、重大项目计划指南、揭榜挂帅技术需求... [目的/意义]立足国家战略需求,构建透明化、规范化、可循证的颠覆性技术量化识别方法。[方法/过程]从颠覆性技术的技术突破和场景牵引来源出发,综合采用科技战略动态、科技前沿动态、权威预测清单、重大项目计划指南、揭榜挂帅技术需求清单、美国实体清单、国际智库报告、新闻舆情、企业融资行为等多源情报数据,利用自主研发的重大科技问题智能态势感知与分析平台,遵循“收敛+凝聚”的研究路线,构建一套颠覆性技术量化识别方法,实现颠覆性技术及其下位细粒度科技问题的准确识别。[结果/结论]经应用实证,上述方法的识别结果与相关权威观点中所提到的颠覆性技术具有较高的重合度,且可提供颠覆性技术下位更细粒度的科技问题列表,识别结果可信、可循证、可追溯。同时,上述方法在战略规划研究、问题清单编制等实际工作场景中已有多次应用,进一步验证了方法和流程的有效性和合理性。 展开更多
关键词 颠覆性技术量化识别 技术突破 场景牵引 多源情报数据 科技问题
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行驶工况下基于MDA-PF的车用锂离子电池剩余寿命预测方法
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作者 李兆军 杨统雨 +2 位作者 周怡昕 吴方明 黄伟 《电源技术》 北大核心 2025年第9期1943-1950,共8页
针对行驶工况下车用锂离子电池容量衰减特性复杂且数据不足的情形,提出了基于数据与模型混合驱动的锂离子电池剩余使用寿命(RUL)预测方法。应用Savitzky-Golay(SG)滤波法对电池容量衰减数据进行平滑降噪;建立多源域自适应(MDA)神经网络... 针对行驶工况下车用锂离子电池容量衰减特性复杂且数据不足的情形,提出了基于数据与模型混合驱动的锂离子电池剩余使用寿命(RUL)预测方法。应用Savitzky-Golay(SG)滤波法对电池容量衰减数据进行平滑降噪;建立多源域自适应(MDA)神经网络,运用多组锂离子电池容量衰减数据预测少样本情况下锂离子电池的RUL;运用粒子滤波(PF)算法将MDA神经网络预测值融入电池容量衰减经验模型的动态估计过程,从而形成可实现行驶工况下锂离子电池RUL预测的MDA-PF方法,并通过实例对所提出的方法进行验证。实验结果表明,使用该方法的预测结果的均方根误差都小于0.13,平均绝对百分比误差均保持在0.07以下,决定系数均在0.98以上,证明了该MDA-PF方法能够有效预测行驶工况下的车用锂离子电池RUL,比其他常用方法具有更好的预测效果。 展开更多
关键词 锂离子电池 剩余使用寿命 粒子滤波 多源域自适应
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