As one of the Special Economic Zones since the reform and opening up, Zhuhai has developed during the past 30 years. Its economic development, industrial structure and ecological environment have undergone great chang...As one of the Special Economic Zones since the reform and opening up, Zhuhai has developed during the past 30 years. Its economic development, industrial structure and ecological environment have undergone great changes. Research on changes in Zhuhai’s land ecological security is of great significance. Using relevant data from 2007-2012, this study established a land ecological security assessment system based on the PSR conceptual framework model. The system contained 18 indicators from 3 aspects according to the concrete features of Zhuhai. Then we used the matterelement analysis and the improved entropy weight to analyze and evaluate the land ecological security of Zhuhai. The results showed that: from 2007 to 2012, the levels of the land ecological security of Zhuhai were “secure”, and the value increased year by year;as the land ecological security response value increased, Zhuhai was capable of solving land ecosystem problems. However, it should be noted that the structure of land ecosystem in Zhuhai has not formed and that rapid expansion of construction land has caused the shortage of cultivated land and other issues. Measures should be taken to control the construction area, improve land intensive utilization and improve the land ecological security.展开更多
Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be so...Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.展开更多
Well logging technology has accumulated a large amount of historical data through four generations of technological development,which forms the basis of well logging big data and digital assets.However,the value of th...Well logging technology has accumulated a large amount of historical data through four generations of technological development,which forms the basis of well logging big data and digital assets.However,the value of these data has not been well stored,managed and mined.With the development of cloud computing technology,it provides a rare development opportunity for logging big data private cloud.The traditional petrophysical evaluation and interpretation model has encountered great challenges in the face of new evaluation objects.The solution research of logging big data distributed storage,processing and learning functions integrated in logging big data private cloud has not been carried out yet.To establish a distributed logging big-data private cloud platform centered on a unifi ed learning model,which achieves the distributed storage and processing of logging big data and facilitates the learning of novel knowledge patterns via the unifi ed logging learning model integrating physical simulation and data models in a large-scale functional space,thus resolving the geo-engineering evaluation problem of geothermal fi elds.Based on the research idea of“logging big data cloud platform-unifi ed logging learning model-large function space-knowledge learning&discovery-application”,the theoretical foundation of unified learning model,cloud platform architecture,data storage and learning algorithm,arithmetic power allocation and platform monitoring,platform stability,data security,etc.have been carried on analysis.The designed logging big data cloud platform realizes parallel distributed storage and processing of data and learning algorithms.The feasibility of constructing a well logging big data cloud platform based on a unifi ed learning model of physics and data is analyzed in terms of the structure,ecology,management and security of the cloud platform.The case study shows that the logging big data cloud platform has obvious technical advantages over traditional logging evaluation methods in terms of knowledge discovery method,data software and results sharing,accuracy,speed and complexity.展开更多
On the basis of the soil environment investigation in Da＇an City, Jilin Province, China, 40 soil samples from main land use types were obtained and tested by standard method. Soil organic matter （SOM）, total N （TN...On the basis of the soil environment investigation in Da＇an City, Jilin Province, China, 40 soil samples from main land use types were obtained and tested by standard method. Soil organic matter （SOM）, total N （TN）, total P （TP）, total K （TK）, available N （AN）, available P （AP） and available K （AK） were chosen as the evaluation factors. A regional soil nutrient evaluation model was developed based on the matter-element model. The results show that the soil samples with nutrient grade Ⅱ-Ⅴ respectively account for 10%, 30%, 32.5% and 27.5%, and those with grade Ⅳ and Ⅴ account for 60% in all samples. The relationship between soil nutrients and land types indicates that the nutrients of farmland are relatively good, with 41.7% of soil samples with the nutrient grade Ⅳ and Ⅴ. The nutrients of saline-alkali land and sandy land are the worst, with 100% of soil samples with the nutrient grade IV and V. And the ratios of soil samples grade IV and V in grassland and wasteland are respectively 62.5 % and 54.55%. Generally speaking, the soil nutrients status in Da＇an City is poor, 60% of soil samples are in poor and extremely poor conditions, indicating that the soil has been severely eroded. Being a relatively superior evaluation method with more accurate resuits and spatial distribution consistency, matter-element analysis is more suitable for regional soil nutrient evaluation than previous models.展开更多
When water environmental carrying capacity of public resource tourist attraction is studied, the two action subjects of tourists and local residents should be discussed, and comprehensive consideration must be given t...When water environmental carrying capacity of public resource tourist attraction is studied, the two action subjects of tourists and local residents should be discussed, and comprehensive consideration must be given to the influence of these two on water environment. On the basis of water resource carrying capacity and water quality carrying capacity, water environmental carrying capacity index of public resource tourist attraction was constructed, the model for the water environmental carrying capacity of public resource tourist attraction was established on the basis of matter-element model and analytical hierarchy process. By applying this method, water environmental carrying capacity situation of a certain public resource tourist attraction can be gained, moreover, situations about several aspects of water environmental carrying capacity can be evaluated.展开更多
The theory and method of extenics were applied to establish classical field matterelements and segment field matter elements for coal and gas outburst.A matter-element model for prediction was established based on fiv...The theory and method of extenics were applied to establish classical field matterelements and segment field matter elements for coal and gas outburst.A matter-element model for prediction was established based on five matter-elements,which includedgas pressure,types of coal damage,coal rigidity,initial speed of methane diffusionand in-situ stress.Each index weight was given fairly and quickly through the improvedanalytic hierarchy process,which need not carry on consistency checks,so accuracy ofassessment can be improved.展开更多
Cloud diurnal variation is crucial for regulating cloud radiative effects and atmospheric dynamics.However,it is often overlooked in the evaluation and development of climate models.Thus,this study aims to investigate...Cloud diurnal variation is crucial for regulating cloud radiative effects and atmospheric dynamics.However,it is often overlooked in the evaluation and development of climate models.Thus,this study aims to investigate the daily mean(CFR)and diurnal variation(CDV)of cloud fraction across high-,middle-,low-level,and total clouds in the FGOALS-f3-L general circulation model.The bias of total CDV is decomposed into the model biases in CFRs and CDVs of clouds at all three levels.Results indicate that the model generally underestimates low-level cloud fraction during the daytime and high-/middle-level cloud fraction at nighttime.The simulation biases of low clouds,especially their CDV biases,dominate the bias of total CDV.Compensation effects exist among the bias decompositions,where the negative contributions of underestimated daytime low-level cloud fraction are partially offset by the opposing contributions from biases in high-/middle-level clouds.Meanwhile,the bias contributions have notable land–ocean differences and region-dependent characteristics,consistent with the model biases in these variables.Additionally,the study estimates the influences of CFR and CDV biases on the bias of shortwave cloud radiative effects.It reveals that the impacts of CDV biases can reach half of those from CFR biases,highlighting the importance of accurate CDV representation in climate models.展开更多
Existing reverse-engineering methods struggle to directly generate editable,parametric CAD models from scanned data.To address this limitation,this paper proposes a reverse-modeling approach that reconstructs parametr...Existing reverse-engineering methods struggle to directly generate editable,parametric CAD models from scanned data.To address this limitation,this paper proposes a reverse-modeling approach that reconstructs parametric CAD models from multi-view RGB-D point clouds.Multi-frame point-cloud registration and fusion are first employed to obtain a complete 3-D point cloud of the target object.A region-growing algorithm that jointly exploits color and geometric information segments the cloud,while RANSAC robustly detects and fits basic geometric primitives.These primitives serve as nodes in a graph whose edge features are inferred by a graph neural network to capture spatial constraints.From the detected primitives and their constraints,a high-accuracy,fully editable parametric CAD model is finally exported.Experiments show an average parameter error of 0.3 mm for key dimensions and an overall geometric reconstruction accuracy of 0.35 mm.The work offers an effective technical route toward automated,intelligent 3-D reverse modeling.展开更多
Pronounced climatic differences occur over subtropical South China(SC)and tropical South China Sea(SCS)and understanding the key cloud-radiation characteristics is essential to simulating East Asian climate.This study...Pronounced climatic differences occur over subtropical South China(SC)and tropical South China Sea(SCS)and understanding the key cloud-radiation characteristics is essential to simulating East Asian climate.This study investigated cloud fractions and cloud radiative effects(CREs)over SC and SCS simulated by CMIP6 atmospheric models.Remarkable differences in cloud-radiation characteristics appeared over these two regions.In observations,considerable amounts of low-middle level clouds and cloud radiative cooling effect appeared over SC.In contrast,high clouds prevailed over SCS,where longwave and shortwave CREs offset each other,resulting in a weaker net cloud radiative effect(NCRE).The models underestimated NCRE over SC mainly due to weaker shortwave CRE and less cloud fractions.Conversely,most models overestimated NCRE over SCS because of stronger shortwave CRE and weaker longwave CRE.Regional CREs were closely linked to their dominant cloud fractions.Both observations and simulations showed a negative spatial correlation between total(low)cloud fraction and shortwave CRE over SC,especially in winter,and exhibited a positive correlation between high cloud fraction and longwave CRE over these two regions.Compared with SCS,most models overestimated the spatial correlation between low(high)cloud fraction and SWCRE(LWCRE)over SC,with larger bias ranges among models,indicating the exaggerated cloud radiative cooling(warming)effect caused by low(high)clouds.Moreover,most models struggled to describe regional ascent and its connection with CREs over SC while they can better reproduce these connections over SCS.This study further suggests that reasonable circulation conditions are crucial to simulating well cloud-radiation characteristics over the East Asian regions.展开更多
DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive...DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive exists in a molten liquid state, where high-temperature gases expand and react in the form of bubble clouds within the liquid explosive;this process is distinctly different from the dynamic crack propagation process observed in the case of solid explosives. In this study, a control model for the reaction evolution of burning-bubble clouds was established to describe the reaction process and quantify the reaction violence of DNAN-based melt-cast explosives, considering the size distribution and activation mechanism of the burning-bubble clouds. The feasibility of the model was verified through experimental results. The results revealed that under geometrically similar conditions, with identical confinement strength and aspect ratio, larger charge structures led to extended initial gas flow and surface burning processes, resulting in greater reaction equivalence and violence at the casing fracture.Under constant charge volume and size, a stronger casing confinement accelerated self-enhanced burning, increasing the internal pressure, reaction degree, and reaction violence. Under a constant casing thickness and radius, higher aspect ratios led to a greater reaction violence at the casing fracture.Moreover, under a constant charge volume and casing thickness, higher aspect ratios resulted in a higher internal pressure, increased reaction degree, and greater reaction violence at the casing fracture. Further,larger ullage volumes extended the reaction evolution time and increased the reaction violence under constant casing dimensions. Through a matching design of the opening threshold of the pressure relief holes and the relief structure area, a stable burning reaction could be maintained until completion,thereby achieving a control of the reaction violence. The proposed model could effectively reflect the effects of the intrinsic burning rate, casing confinement strength, charge size, ullage volume, and pressure relief structure on the reaction evolution process and reaction violence, providing a theoretical method for the thermal safety design and reaction violence evaluation of melt-cast explosives.展开更多
The spatial distribution of discontinuities and the size of rock blocks are the key indicators for rock mass quality evaluation and rockfall risk assessment.Traditional manual measurement is often dangerous or unreach...The spatial distribution of discontinuities and the size of rock blocks are the key indicators for rock mass quality evaluation and rockfall risk assessment.Traditional manual measurement is often dangerous or unreachable at some high-steep rock slopes.In contrast,unmanned aerial vehicle(UAV)photogrammetry is not limited by terrain conditions,and can efficiently collect high-precision three-dimensional(3D)point clouds of rock masses through all-round and multiangle photography for rock mass characterization.In this paper,a new method based on a 3D point cloud is proposed for discontinuity identification and refined rock block modeling.The method is based on four steps:(1)Establish a point cloud spatial topology,and calculate the point cloud normal vector and average point spacing based on several machine learning algorithms;(2)Extract discontinuities using the density-based spatial clustering of applications with noise(DBSCAN)algorithm and fit the discontinuity plane by combining principal component analysis(PCA)with the natural breaks(NB)method;(3)Propose a method of inserting points in the line segment to generate an embedded discontinuity point cloud;and(4)Adopt a Poisson reconstruction method for refined rock block modeling.The proposed method was applied to an outcrop of an ultrahigh steep rock slope and compared with the results of previous studies and manual surveys.The results show that the method can eliminate the influence of discontinuity undulations on the orientation measurement and describe the local concave-convex characteristics on the modeling of rock blocks.The calculation results are accurate and reliable,which can meet the practical requirements of engineering.展开更多
The article analyses several key issues which restrict the effectiveness of fund project peer review work. It analyses the evaluating theory and matter-element theory to access the expert anti-evaluation model, and al...The article analyses several key issues which restrict the effectiveness of fund project peer review work. It analyses the evaluating theory and matter-element theory to access the expert anti-evaluation model, and also studies the expert anti-evaluation index system to support the anti-evaluation method. The practical basis is the true score data of the experts which is collected from the actual anti-evaluation in Liaoning province science and technology fund project peer review system. With the practical experience of the actual project, we prove that the expert index system anti-evaluation model and expert anti-evaluation method can improve the fund project peer review work and play a positive role for the peer review work and also make the review work more scientific and more rational.展开更多
The method of cloud model with entropy weight was adopted for the prediction of rock burst classification. Some main factors of rock burst including the uniaxial compressive strength （σc）, the tensile strength （σ...The method of cloud model with entropy weight was adopted for the prediction of rock burst classification. Some main factors of rock burst including the uniaxial compressive strength （σc）, the tensile strength （σt）, the tangential stress （σθ）, the rock brittleness coefficient （σc/σt）, the stress coefficient （σθ /σc） and the elastic energy index （Wet） are chosen to establish evaluation index system. The entropy？cloud model and criterion are obtained through 209 sets of rock burst samples from underground rock projects. The sensitivity of indicators is analyzed and 209 sets of rock burst samples are discriminated by this model. The discriminant results of the entropy-cloud model are compared with those of Bayes, KNN and RF methods. The results show that the sensitivity order of those factors from high to low is σ_θ /σ_c, σ_θ, W_（ct）, σ_c/σ_t, σ_t, σ_c, and the entropy-cloud model has higher accuracy than Bayes, K-Nearest Neighbor algorithm （KNN） and Random Forest （RF） methods.展开更多
Aiming at the real-time fluctuation and nonlinear characteristics of the expressway short-term traffic flow forecasting the parameter projection pursuit regression PPPR model is applied to forecast the expressway traf...Aiming at the real-time fluctuation and nonlinear characteristics of the expressway short-term traffic flow forecasting the parameter projection pursuit regression PPPR model is applied to forecast the expressway traffic flow where the orthogonal Hermite polynomial is used to fit the ridge functions and the least square method is employed to determine the polynomial weight coefficient c.In order to efficiently optimize the projection direction a and the number M of ridge functions of the PPPR model the chaos cloud particle swarm optimization CCPSO algorithm is applied to optimize the parameters. The CCPSO-PPPR hybrid optimization model for expressway short-term traffic flow forecasting is established in which the CCPSO algorithm is used to optimize the optimal projection direction a in the inner layer while the number M of ridge functions is optimized in the outer layer.Traffic volume weather factors and travel date of the previous several time intervals of the road section are taken as the input influencing factors. Example forecasting and model comparison results indicate that the proposed model can obtain a better forecasting effect and its absolute error is controlled within [-6,6] which can meet the application requirements of expressway traffic flow forecasting.展开更多
Model reconstruction from points scanned on existing physical objects is much important in a variety of situations such as reverse engineering for mechanical products, computer vision and recovery of biological shapes...Model reconstruction from points scanned on existing physical objects is much important in a variety of situations such as reverse engineering for mechanical products, computer vision and recovery of biological shapes from two dimensional contours. With the development of measuring equipment, cloud points that contain more details of the object can be obtained conveniently. On the other hand, large quantity of sampled points brings difficulties to model reconstruction method. This paper first presents an algorithm to automatically reduce the number of cloud points under given tolerance. Triangle mesh surface from the simplified data set is reconstructed by the marching cubes algorithm. For various reasons, reconstructed mesh usually contains unwanted holes. An approach to create new triangles is proposed with optimized shape for covering the unexpected holes in triangle meshes. After hole filling, watertight triangle mesh can be directly output in STL format, which is widely used in rapid prototype manufacturing. Practical examples are included to demonstrate the method.展开更多
In order to reduce amount of data storage and improve processing capacity of the system, this paper proposes a new classification method of data source by combining phase synchronization model in network clusteri...In order to reduce amount of data storage and improve processing capacity of the system, this paper proposes a new classification method of data source by combining phase synchronization model in network clustering with cloud model. Firstly, taking data source as a complex network, after the topography of network is obtained, the cloud model of each node data is determined by fuzzy analytic hierarchy process （AHP）. Secondly, by calculating expectation, entropy and hyper entropy of the cloud model, comprehensive coupling strength is got and then it is regarded as the edge weight of topography. Finally, distribution curve is obtained by iterating the phase of each node by means of phase synchronization model. Thus classification of data source is completed. This method can not only provide convenience for storage, cleaning and compression of data, but also improve the efficiency of data analysis.展开更多
Rapid urbanization has led to a surge in the number of towering structures,and overturning is widely used because it can better accommodate the construction of shaped structures such as variable sections.The complexit...Rapid urbanization has led to a surge in the number of towering structures,and overturning is widely used because it can better accommodate the construction of shaped structures such as variable sections.The complexity of the construction process makes the construction risk have certain randomness,so this paper proposes a cloudbased coupled matter-element model to address the ambiguity and randomness in the safety risk assessment of overturning construction of towering structures.In the pretended model,the digital eigenvalues of the cloud model are used to replace the eigenvalues in the matter–element basic element,and calculate the cloud correlation of the risk assessment metrics through the correlation algorithm of the cloud model to build the computational model.Meanwhile,the improved hierarchical analysis method based on the cloud model is used to determine the weight of the index.The comprehensive evaluation scores of the evaluation event are then obtained through the weighted average method,and the safety risk level is determined accordingly.Through empirical analysis,(1)the improved hierarchical analysis method based on the cloud model can incorporate the data of multiple decisionmakers into the calculation formula to determine theweights,which makes the assessment resultsmore credible;(2)the evaluation results of the cloud-basedmatter-element coupledmodelmethod are basically consistent with those of the other two commonly used methods,and the confidence factor is less than 0.05,indicating that the cloudbased physical element coupled model method is reasonable and practical for towering structure overturning;(3)the cloud-based coupled element model method,which confirms the reliability of risk level by performing Spearman correlation on comprehensive assessment scores,can provide more comprehensive information of instances compared with other methods,and more comprehensively reflects the fuzzy uncertainty relationship between assessment indexes,which makes the assessment results more realistic,scientific and reliable.展开更多
Recommender system is an important content in the research of E-commerce technology. Collaborative filtering recom-mendation algorithm has already been used successfully at recom-mender system. However,with the develo...Recommender system is an important content in the research of E-commerce technology. Collaborative filtering recom-mendation algorithm has already been used successfully at recom-mender system. However,with the development of E-commerce,the difficulties of the extreme sparsity of user rating data have become more and more severe. Based on the traditional similarity measuring methods,we introduce the cloud model and combine it with the item-based collaborative filtering recommendation algorithms. The new collaborative filtering recommendation algorithm based on item and cloud model （IC-Based CF） computes the similarity de-gree between items by comparing the statistical characteristic of items. The experimental results show that this method can improve the performance of the present item-based collaborative filtering algorithm with extreme sparsity of data.展开更多
The motion of particle clouds formed by dumping dredged material into quiescent waters is experimentally and numerically studied. In the numerical model, the particle phase is modeled by the dispersion model, and turb...The motion of particle clouds formed by dumping dredged material into quiescent waters is experimentally and numerically studied. In the numerical model, the particle phase is modeled by the dispersion model, and turbulence is calculated by the large eddy simulation. The governing equations, including the filtered Navier-Stokes equations and mass transport equation, are solved based on the operator-splitting algorithm and an implicit cubic spline interpolation scheme. The eddy viscosity is evaluated by the modified Smagorinsky model including the buoyancy term. Comparisons of main flow characteristics, including shape, size, average density excess, moving speed and the amount of particles deposited on the bed, between experimental and computational results show that the numerical model well predicts the motion of the cloud from the falling to spreading stage. The effects of silt-fence on the motion of the particle cloud are also investigated.展开更多
文摘As one of the Special Economic Zones since the reform and opening up, Zhuhai has developed during the past 30 years. Its economic development, industrial structure and ecological environment have undergone great changes. Research on changes in Zhuhai’s land ecological security is of great significance. Using relevant data from 2007-2012, this study established a land ecological security assessment system based on the PSR conceptual framework model. The system contained 18 indicators from 3 aspects according to the concrete features of Zhuhai. Then we used the matterelement analysis and the improved entropy weight to analyze and evaluate the land ecological security of Zhuhai. The results showed that: from 2007 to 2012, the levels of the land ecological security of Zhuhai were “secure”, and the value increased year by year;as the land ecological security response value increased, Zhuhai was capable of solving land ecosystem problems. However, it should be noted that the structure of land ecosystem in Zhuhai has not formed and that rapid expansion of construction land has caused the shortage of cultivated land and other issues. Measures should be taken to control the construction area, improve land intensive utilization and improve the land ecological security.
基金Heilongjiang Provincial Natural Science Foundation of China (LH2021F009)。
文摘Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.
基金supported By Grant (PLN2022-14) of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Southwest Petroleum University)。
文摘Well logging technology has accumulated a large amount of historical data through four generations of technological development,which forms the basis of well logging big data and digital assets.However,the value of these data has not been well stored,managed and mined.With the development of cloud computing technology,it provides a rare development opportunity for logging big data private cloud.The traditional petrophysical evaluation and interpretation model has encountered great challenges in the face of new evaluation objects.The solution research of logging big data distributed storage,processing and learning functions integrated in logging big data private cloud has not been carried out yet.To establish a distributed logging big-data private cloud platform centered on a unifi ed learning model,which achieves the distributed storage and processing of logging big data and facilitates the learning of novel knowledge patterns via the unifi ed logging learning model integrating physical simulation and data models in a large-scale functional space,thus resolving the geo-engineering evaluation problem of geothermal fi elds.Based on the research idea of“logging big data cloud platform-unifi ed logging learning model-large function space-knowledge learning&discovery-application”,the theoretical foundation of unified learning model,cloud platform architecture,data storage and learning algorithm,arithmetic power allocation and platform monitoring,platform stability,data security,etc.have been carried on analysis.The designed logging big data cloud platform realizes parallel distributed storage and processing of data and learning algorithms.The feasibility of constructing a well logging big data cloud platform based on a unifi ed learning model of physics and data is analyzed in terms of the structure,ecology,management and security of the cloud platform.The case study shows that the logging big data cloud platform has obvious technical advantages over traditional logging evaluation methods in terms of knowledge discovery method,data software and results sharing,accuracy,speed and complexity.
基金Under the auspices of National Natural Science Foundation of China (No. 40572170, 40871088 )
文摘On the basis of the soil environment investigation in Da＇an City, Jilin Province, China, 40 soil samples from main land use types were obtained and tested by standard method. Soil organic matter （SOM）, total N （TN）, total P （TP）, total K （TK）, available N （AN）, available P （AP） and available K （AK） were chosen as the evaluation factors. A regional soil nutrient evaluation model was developed based on the matter-element model. The results show that the soil samples with nutrient grade Ⅱ-Ⅴ respectively account for 10%, 30%, 32.5% and 27.5%, and those with grade Ⅳ and Ⅴ account for 60% in all samples. The relationship between soil nutrients and land types indicates that the nutrients of farmland are relatively good, with 41.7% of soil samples with the nutrient grade Ⅳ and Ⅴ. The nutrients of saline-alkali land and sandy land are the worst, with 100% of soil samples with the nutrient grade IV and V. And the ratios of soil samples grade IV and V in grassland and wasteland are respectively 62.5 % and 54.55%. Generally speaking, the soil nutrients status in Da＇an City is poor, 60% of soil samples are in poor and extremely poor conditions, indicating that the soil has been severely eroded. Being a relatively superior evaluation method with more accurate resuits and spatial distribution consistency, matter-element analysis is more suitable for regional soil nutrient evaluation than previous models.
文摘When water environmental carrying capacity of public resource tourist attraction is studied, the two action subjects of tourists and local residents should be discussed, and comprehensive consideration must be given to the influence of these two on water environment. On the basis of water resource carrying capacity and water quality carrying capacity, water environmental carrying capacity index of public resource tourist attraction was constructed, the model for the water environmental carrying capacity of public resource tourist attraction was established on the basis of matter-element model and analytical hierarchy process. By applying this method, water environmental carrying capacity situation of a certain public resource tourist attraction can be gained, moreover, situations about several aspects of water environmental carrying capacity can be evaluated.
基金Supported by the National Natural Science Foundation of China(50534080)the Science and Technology Research Project of Chongqing(CSCT,2006AA7002)
文摘The theory and method of extenics were applied to establish classical field matterelements and segment field matter elements for coal and gas outburst.A matter-element model for prediction was established based on five matter-elements,which includedgas pressure,types of coal damage,coal rigidity,initial speed of methane diffusionand in-situ stress.Each index weight was given fairly and quickly through the improvedanalytic hierarchy process,which need not carry on consistency checks,so accuracy ofassessment can be improved.
基金supported by the National Natural Science Foundation of China[grant number 42275074].
文摘Cloud diurnal variation is crucial for regulating cloud radiative effects and atmospheric dynamics.However,it is often overlooked in the evaluation and development of climate models.Thus,this study aims to investigate the daily mean(CFR)and diurnal variation(CDV)of cloud fraction across high-,middle-,low-level,and total clouds in the FGOALS-f3-L general circulation model.The bias of total CDV is decomposed into the model biases in CFRs and CDVs of clouds at all three levels.Results indicate that the model generally underestimates low-level cloud fraction during the daytime and high-/middle-level cloud fraction at nighttime.The simulation biases of low clouds,especially their CDV biases,dominate the bias of total CDV.Compensation effects exist among the bias decompositions,where the negative contributions of underestimated daytime low-level cloud fraction are partially offset by the opposing contributions from biases in high-/middle-level clouds.Meanwhile,the bias contributions have notable land–ocean differences and region-dependent characteristics,consistent with the model biases in these variables.Additionally,the study estimates the influences of CFR and CDV biases on the bias of shortwave cloud radiative effects.It reveals that the impacts of CDV biases can reach half of those from CFR biases,highlighting the importance of accurate CDV representation in climate models.
文摘Existing reverse-engineering methods struggle to directly generate editable,parametric CAD models from scanned data.To address this limitation,this paper proposes a reverse-modeling approach that reconstructs parametric CAD models from multi-view RGB-D point clouds.Multi-frame point-cloud registration and fusion are first employed to obtain a complete 3-D point cloud of the target object.A region-growing algorithm that jointly exploits color and geometric information segments the cloud,while RANSAC robustly detects and fits basic geometric primitives.These primitives serve as nodes in a graph whose edge features are inferred by a graph neural network to capture spatial constraints.From the detected primitives and their constraints,a high-accuracy,fully editable parametric CAD model is finally exported.Experiments show an average parameter error of 0.3 mm for key dimensions and an overall geometric reconstruction accuracy of 0.35 mm.The work offers an effective technical route toward automated,intelligent 3-D reverse modeling.
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)National Natural Science Foundation of China(72293604,42275026)Open Grants of the State Key Laboratory of Severe Weather(2023LASW-B09)。
文摘Pronounced climatic differences occur over subtropical South China(SC)and tropical South China Sea(SCS)and understanding the key cloud-radiation characteristics is essential to simulating East Asian climate.This study investigated cloud fractions and cloud radiative effects(CREs)over SC and SCS simulated by CMIP6 atmospheric models.Remarkable differences in cloud-radiation characteristics appeared over these two regions.In observations,considerable amounts of low-middle level clouds and cloud radiative cooling effect appeared over SC.In contrast,high clouds prevailed over SCS,where longwave and shortwave CREs offset each other,resulting in a weaker net cloud radiative effect(NCRE).The models underestimated NCRE over SC mainly due to weaker shortwave CRE and less cloud fractions.Conversely,most models overestimated NCRE over SCS because of stronger shortwave CRE and weaker longwave CRE.Regional CREs were closely linked to their dominant cloud fractions.Both observations and simulations showed a negative spatial correlation between total(low)cloud fraction and shortwave CRE over SC,especially in winter,and exhibited a positive correlation between high cloud fraction and longwave CRE over these two regions.Compared with SCS,most models overestimated the spatial correlation between low(high)cloud fraction and SWCRE(LWCRE)over SC,with larger bias ranges among models,indicating the exaggerated cloud radiative cooling(warming)effect caused by low(high)clouds.Moreover,most models struggled to describe regional ascent and its connection with CREs over SC while they can better reproduce these connections over SCS.This study further suggests that reasonable circulation conditions are crucial to simulating well cloud-radiation characteristics over the East Asian regions.
基金supported by the National Natural Science Foundation of China (Grant No. 12002044)。
文摘DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive exists in a molten liquid state, where high-temperature gases expand and react in the form of bubble clouds within the liquid explosive;this process is distinctly different from the dynamic crack propagation process observed in the case of solid explosives. In this study, a control model for the reaction evolution of burning-bubble clouds was established to describe the reaction process and quantify the reaction violence of DNAN-based melt-cast explosives, considering the size distribution and activation mechanism of the burning-bubble clouds. The feasibility of the model was verified through experimental results. The results revealed that under geometrically similar conditions, with identical confinement strength and aspect ratio, larger charge structures led to extended initial gas flow and surface burning processes, resulting in greater reaction equivalence and violence at the casing fracture.Under constant charge volume and size, a stronger casing confinement accelerated self-enhanced burning, increasing the internal pressure, reaction degree, and reaction violence. Under a constant casing thickness and radius, higher aspect ratios led to a greater reaction violence at the casing fracture.Moreover, under a constant charge volume and casing thickness, higher aspect ratios resulted in a higher internal pressure, increased reaction degree, and greater reaction violence at the casing fracture. Further,larger ullage volumes extended the reaction evolution time and increased the reaction violence under constant casing dimensions. Through a matching design of the opening threshold of the pressure relief holes and the relief structure area, a stable burning reaction could be maintained until completion,thereby achieving a control of the reaction violence. The proposed model could effectively reflect the effects of the intrinsic burning rate, casing confinement strength, charge size, ullage volume, and pressure relief structure on the reaction evolution process and reaction violence, providing a theoretical method for the thermal safety design and reaction violence evaluation of melt-cast explosives.
基金supported by the National Natural Science Foundation of China(Grant Nos.41941017 and 42177139)Graduate Innovation Fund of Jilin University(Grant No.2024CX099)。
文摘The spatial distribution of discontinuities and the size of rock blocks are the key indicators for rock mass quality evaluation and rockfall risk assessment.Traditional manual measurement is often dangerous or unreachable at some high-steep rock slopes.In contrast,unmanned aerial vehicle(UAV)photogrammetry is not limited by terrain conditions,and can efficiently collect high-precision three-dimensional(3D)point clouds of rock masses through all-round and multiangle photography for rock mass characterization.In this paper,a new method based on a 3D point cloud is proposed for discontinuity identification and refined rock block modeling.The method is based on four steps:(1)Establish a point cloud spatial topology,and calculate the point cloud normal vector and average point spacing based on several machine learning algorithms;(2)Extract discontinuities using the density-based spatial clustering of applications with noise(DBSCAN)algorithm and fit the discontinuity plane by combining principal component analysis(PCA)with the natural breaks(NB)method;(3)Propose a method of inserting points in the line segment to generate an embedded discontinuity point cloud;and(4)Adopt a Poisson reconstruction method for refined rock block modeling.The proposed method was applied to an outcrop of an ultrahigh steep rock slope and compared with the results of previous studies and manual surveys.The results show that the method can eliminate the influence of discontinuity undulations on the orientation measurement and describe the local concave-convex characteristics on the modeling of rock blocks.The calculation results are accurate and reliable,which can meet the practical requirements of engineering.
文摘The article analyses several key issues which restrict the effectiveness of fund project peer review work. It analyses the evaluating theory and matter-element theory to access the expert anti-evaluation model, and also studies the expert anti-evaluation index system to support the anti-evaluation method. The practical basis is the true score data of the experts which is collected from the actual anti-evaluation in Liaoning province science and technology fund project peer review system. With the practical experience of the actual project, we prove that the expert index system anti-evaluation model and expert anti-evaluation method can improve the fund project peer review work and play a positive role for the peer review work and also make the review work more scientific and more rational.
基金Projects(51474252,51274253)supported by the National Natural Science Foundation of ChinaProject(2015CX005)supported by the Innovation Driven Plan of Central South University,ChinaProject(2016zzts095)supported by the Fundamental Research Funds for the Central Universities,China
文摘The method of cloud model with entropy weight was adopted for the prediction of rock burst classification. Some main factors of rock burst including the uniaxial compressive strength （σc）, the tensile strength （σt）, the tangential stress （σθ）, the rock brittleness coefficient （σc/σt）, the stress coefficient （σθ /σc） and the elastic energy index （Wet） are chosen to establish evaluation index system. The entropy？cloud model and criterion are obtained through 209 sets of rock burst samples from underground rock projects. The sensitivity of indicators is analyzed and 209 sets of rock burst samples are discriminated by this model. The discriminant results of the entropy-cloud model are compared with those of Bayes, KNN and RF methods. The results show that the sensitivity order of those factors from high to low is σ_θ /σ_c, σ_θ, W_（ct）, σ_c/σ_t, σ_t, σ_c, and the entropy-cloud model has higher accuracy than Bayes, K-Nearest Neighbor algorithm （KNN） and Random Forest （RF） methods.
基金The National Natural Science Foundation of China(No.71101014,50679008)Specialized Research Fund for the Doctoral Program of Higher Education(No.200801411105)the Science and Technology Project of the Department of Communications of Henan Province(No.2010D107-4)
文摘Aiming at the real-time fluctuation and nonlinear characteristics of the expressway short-term traffic flow forecasting the parameter projection pursuit regression PPPR model is applied to forecast the expressway traffic flow where the orthogonal Hermite polynomial is used to fit the ridge functions and the least square method is employed to determine the polynomial weight coefficient c.In order to efficiently optimize the projection direction a and the number M of ridge functions of the PPPR model the chaos cloud particle swarm optimization CCPSO algorithm is applied to optimize the parameters. The CCPSO-PPPR hybrid optimization model for expressway short-term traffic flow forecasting is established in which the CCPSO algorithm is used to optimize the optimal projection direction a in the inner layer while the number M of ridge functions is optimized in the outer layer.Traffic volume weather factors and travel date of the previous several time intervals of the road section are taken as the input influencing factors. Example forecasting and model comparison results indicate that the proposed model can obtain a better forecasting effect and its absolute error is controlled within [-6,6] which can meet the application requirements of expressway traffic flow forecasting.
文摘Model reconstruction from points scanned on existing physical objects is much important in a variety of situations such as reverse engineering for mechanical products, computer vision and recovery of biological shapes from two dimensional contours. With the development of measuring equipment, cloud points that contain more details of the object can be obtained conveniently. On the other hand, large quantity of sampled points brings difficulties to model reconstruction method. This paper first presents an algorithm to automatically reduce the number of cloud points under given tolerance. Triangle mesh surface from the simplified data set is reconstructed by the marching cubes algorithm. For various reasons, reconstructed mesh usually contains unwanted holes. An approach to create new triangles is proposed with optimized shape for covering the unexpected holes in triangle meshes. After hole filling, watertight triangle mesh can be directly output in STL format, which is widely used in rapid prototype manufacturing. Practical examples are included to demonstrate the method.
基金National Natural Science Foundation of China(No.61171057,No.61503345)Science Foundation for North University of China(No.110246)+1 种基金Specialized Research Fund for Doctoral Program of Higher Education of China(No.20121420110004)International Office of Shanxi Province Education Department of China,and Basic Research Project in Shanxi Province(Young Foundation)
文摘In order to reduce amount of data storage and improve processing capacity of the system, this paper proposes a new classification method of data source by combining phase synchronization model in network clustering with cloud model. Firstly, taking data source as a complex network, after the topography of network is obtained, the cloud model of each node data is determined by fuzzy analytic hierarchy process （AHP）. Secondly, by calculating expectation, entropy and hyper entropy of the cloud model, comprehensive coupling strength is got and then it is regarded as the edge weight of topography. Finally, distribution curve is obtained by iterating the phase of each node by means of phase synchronization model. Thus classification of data source is completed. This method can not only provide convenience for storage, cleaning and compression of data, but also improve the efficiency of data analysis.
基金funded by China Railway No.21 Bureau Group No.1 Engineering Co.,Ltd.,Grant No.202209140002.
文摘Rapid urbanization has led to a surge in the number of towering structures,and overturning is widely used because it can better accommodate the construction of shaped structures such as variable sections.The complexity of the construction process makes the construction risk have certain randomness,so this paper proposes a cloudbased coupled matter-element model to address the ambiguity and randomness in the safety risk assessment of overturning construction of towering structures.In the pretended model,the digital eigenvalues of the cloud model are used to replace the eigenvalues in the matter–element basic element,and calculate the cloud correlation of the risk assessment metrics through the correlation algorithm of the cloud model to build the computational model.Meanwhile,the improved hierarchical analysis method based on the cloud model is used to determine the weight of the index.The comprehensive evaluation scores of the evaluation event are then obtained through the weighted average method,and the safety risk level is determined accordingly.Through empirical analysis,(1)the improved hierarchical analysis method based on the cloud model can incorporate the data of multiple decisionmakers into the calculation formula to determine theweights,which makes the assessment resultsmore credible;(2)the evaluation results of the cloud-basedmatter-element coupledmodelmethod are basically consistent with those of the other two commonly used methods,and the confidence factor is less than 0.05,indicating that the cloudbased physical element coupled model method is reasonable and practical for towering structure overturning;(3)the cloud-based coupled element model method,which confirms the reliability of risk level by performing Spearman correlation on comprehensive assessment scores,can provide more comprehensive information of instances compared with other methods,and more comprehensively reflects the fuzzy uncertainty relationship between assessment indexes,which makes the assessment results more realistic,scientific and reliable.
基金Supported by the National Basic Research Program of China (973 Program) (2006CB701305, 2007CB310804)the National Natural Science Foundation of China (60743001)+1 种基金Best National Thesis Fund (2005047)the Natural Science Foundation of Hubei Province (CDB132, 2010j0049)
文摘Recommender system is an important content in the research of E-commerce technology. Collaborative filtering recom-mendation algorithm has already been used successfully at recom-mender system. However,with the development of E-commerce,the difficulties of the extreme sparsity of user rating data have become more and more severe. Based on the traditional similarity measuring methods,we introduce the cloud model and combine it with the item-based collaborative filtering recommendation algorithms. The new collaborative filtering recommendation algorithm based on item and cloud model （IC-Based CF） computes the similarity de-gree between items by comparing the statistical characteristic of items. The experimental results show that this method can improve the performance of the present item-based collaborative filtering algorithm with extreme sparsity of data.
基金This study was supported by the Grant-in-Aid for Science Research of the Ministry of Education and Culture, Japan, under the Grant No. 08455232.
文摘The motion of particle clouds formed by dumping dredged material into quiescent waters is experimentally and numerically studied. In the numerical model, the particle phase is modeled by the dispersion model, and turbulence is calculated by the large eddy simulation. The governing equations, including the filtered Navier-Stokes equations and mass transport equation, are solved based on the operator-splitting algorithm and an implicit cubic spline interpolation scheme. The eddy viscosity is evaluated by the modified Smagorinsky model including the buoyancy term. Comparisons of main flow characteristics, including shape, size, average density excess, moving speed and the amount of particles deposited on the bed, between experimental and computational results show that the numerical model well predicts the motion of the cloud from the falling to spreading stage. The effects of silt-fence on the motion of the particle cloud are also investigated.
