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
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 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
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
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
With a focus on the difficulty of quantitatively describing the degree of nonuniformity of temporal and spatial distributions of water resources, quantitative research was carried out on the temporal and spatial distr...With a focus on the difficulty of quantitatively describing the degree of nonuniformity of temporal and spatial distributions of water resources, quantitative research was carried out on the temporal and spatial distribution characteristics of water resources in Guangdong Province from 1956 to 2000 based on a cloud model. The spatial variation of the temporal distribution characteristics and the temporal variation of the spatial distribution characteristics were both analyzed. In addition, the relationships between the numerical characteristics of the cloud model of temporal and spatial distributions of water resources and precipitation were also studied. The results show that, using a cloud model, it is possible to intuitively describe the temporal and spatial distribution characteristics of water resources in cloud images. Water resources in Guangdong Province and their temporal and spatial distribution characteristics are differentiated by their geographic locations. Downstream and coastal areas have a larger amount of water resources with greater uniformity and stronger stability in terms of temporal distribution. Regions with more precipitation possess larger amounts of water resources, and years with more precipitation show greater nonuniformity in the spatial distribution of water resources. The correlation between the nonuniformity of the temporal distribution and local precipitation is small, and no correlation is found between the stability of the nonuniformity of the temporal and spatial distributions of water resources and precipitation. The amount of water resources in Guangdong Province shows an increasing trend from 1956 to 2000, the nonuniformity of the spatial distribution of water resources declines, and the stability of the nonuniformity of the spatial distribution of water resources is enhanced.展开更多
The veracity of land evaluation is tightly related to the reasonable weights of land evaluation fac- tors. By mapping qualitative linguistic words into a fine-changeable cloud drops and translating the uncertain facto...The veracity of land evaluation is tightly related to the reasonable weights of land evaluation fac- tors. By mapping qualitative linguistic words into a fine-changeable cloud drops and translating the uncertain factor conditions into quantitative values with the uncertain illation based on cloud model, and then, inte- grating correlation analysis, a new way of figuring out the weight of land evaluation factors is proposed. It may solve the limitations of the conventional ways.展开更多
Uncertainties existing in the process of dam deformation negatively influence deformation prediction.However,existing deformation pre-diction models seldom consider uncertainties.In this study,a cloud-Verhulst hybrid ...Uncertainties existing in the process of dam deformation negatively influence deformation prediction.However,existing deformation pre-diction models seldom consider uncertainties.In this study,a cloud-Verhulst hybrid prediction model was established by combing a cloud model with the Verhulst model.The expectation,one of the cloud characteristic parameters,was obtained using the Verhulst model,and the other two cloud characteristic parameters,entropy and hyper-entropy,were calculated by introducing inertia weight.The hybrid prediction model was used to predict the dam deformation in a hydroelectric project.Comparison of the prediction results of the hybrid prediction model with those of a traditional statistical model and the monitoring values shows that the proposed model has higher prediction accuracy than the traditional sta-tistical model.It provides a new approach to predicting dam deformation under uncertain conditions.展开更多
Ventilation system is significant in underground metal mine of alpine region.Reasonable evaluation of ventilation effectiveness will lead to a practical improvement for the maintenance and management of ventilation sy...Ventilation system is significant in underground metal mine of alpine region.Reasonable evaluation of ventilation effectiveness will lead to a practical improvement for the maintenance and management of ventilation system.However,it is difficult to make an effective evaluation of ventilation system due to the lack of classification criteria with respect to underground metal mine in alpine region.This paper proposes a novel evaluation method called the cloud model-clustering analysis(CMCA).Cloud model(CM)is utilized to process collected data of ventilation system,and they are converted into cloud descriptors by CM.Cloud similarity(CS)based Euclidean distance(ED)is proposed to make clustering analysis of assessed samples.Then the classification of assessed samples will be identified by clustering analysis results.A case study is developed based on CMCA.Evaluation results show that ventilation effectiveness can be well classified.Moreover,CM is used alone to make comparison of evaluation results obtained by CMCA.Then the availability and validity of CMCA is verified.Meanwhile,difference of CS based ED and classical ED is analyzed.Two new clustering analysis methods are introduced to make comparison with CMCA.Then the ability of proposed CMCA to meet evaluation requirements of ventilation system is verified.展开更多
Time series prediction has been successfully used in several application areas, such as meteoro-logical forecasting, market prediction, network traffic forecasting, etc. , and a number of techniques have been develop...Time series prediction has been successfully used in several application areas, such as meteoro-logical forecasting, market prediction, network traffic forecasting, etc. , and a number of techniques have been developed for modeling and predicting time series. In the traditional exponential smoothing method, a fixed weight is assigned to data history, and the trend changes of time series are ignored. In this paper, an uncertainty reasoning method, based on cloud model, is employed in time series prediction, which uses cloud logic controller to adjust the smoothing coefficient of the simple exponential smoothing method dynamically to fit the current trend of the time series. The validity of this solution was proved by experiments on various data sets.展开更多
Mine closure is associated with many negative impacts on society and the environment.If these effects are not rationally addressed,they would pose risks of mine closure.Thus,a risk management method is needed to mitig...Mine closure is associated with many negative impacts on society and the environment.If these effects are not rationally addressed,they would pose risks of mine closure.Thus,a risk management method is needed to mitigate these adverse impacts and address mine-closure issues.An integral framework for mine-closure risk management that includes risk assessment and risk treatment was proposed.Given the fuzziness and randomness of the transformation between qualitative and quantitative knowledge in the risk assessment process,a novel risk assessment method based on the cloud model was presented,which fully considers the uncertainty in risks themselves and in the reasoning process.Closed mine reutilization is an effective risk treatment option in response to the identified high risks,but it requires selecting optimal reutilization strategies for the successful implementation of the reuse plan.To this end,a hybrid semi-quantitative decision method is proposed to optimize decision-making.The results of a case study showed that this risk management methodology can help budget planning for risk treatment and provide an instructional framework to effectively reduce the negative effects of closed mines.展开更多
Safety evaluation of toppling rock slopes developing in reservoir areas is crucial. To reduce the uncertainty of safety evaluation, this study developed a composite cloud model, which improved the combination weights ...Safety evaluation of toppling rock slopes developing in reservoir areas is crucial. To reduce the uncertainty of safety evaluation, this study developed a composite cloud model, which improved the combination weights of the decision-making trial and evaluation laboratory (DEMATEL) and criteria importance through intercriteria correlation (CRITIC) methods. A safety evaluation system was developed according to in situ monitoring data. The backward cloud generator was used to calculate the numerical characteristics of a cloud model of quantitative indices, and different virtual clouds were used to synthesize some clouds into a generalized one. The synthesized numerical characteristics were calculated to comprehensively evaluate the safety of toppling rock slopes. A case study of a toppling rock slope near the Huangdeng Hydropower Station in China was conducted using monitoring data collected since operation of the hydropower project began. The results indicated that the toppling rock slope was moderately safe with a low safety margin. The composite cloud model considers the fuzziness and randomness of safety evaluation and enables interchange between qualitative and quantitative knowledge. This study provides a new theoretical method for evaluating the safety of toppling rock slopes. It can aid in the predication, control, and even prevention of disasters.展开更多
With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distributi...With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.展开更多
In ships having two rudders, an angle error exists if there is a difference in structural and electrical parameters in two steering gear systems. Such an error also results in reduced efficiency of ship maneuverabilit...In ships having two rudders, an angle error exists if there is a difference in structural and electrical parameters in two steering gear systems. Such an error also results in reduced efficiency of ship maneuverability during navigation. For the sake of reducing the angle error, a synchro-ballistic control approach based on cloud model is proposed in this paper. First, the mechanism model of steering gear system is introduced. Second, the structure of synchro-control system of twin-rudder is proposed based on the master-slave control strategy. Third, synchro-ballistic controller based on cloud model is designed to solve the nonlinearity and uncertainty of system. Finally, the designed controller is tested via simulation under two different situations. The simulated results demonstrate that this method is simple and has stronger robustness against the variation of states and parameters of plants. Hence, the validity and reliability of the method is proved for synchro-control of two rudders, which is a significant engineering application.展开更多
In e-commerce, a critical problem is how to transship the products between different e-shops to lessen the risk of out of stock, especially in network shopping mall of China. Most of importance is how to select the op...In e-commerce, a critical problem is how to transship the products between different e-shops to lessen the risk of out of stock, especially in network shopping mall of China. Most of importance is how to select the optimal one in the waiting list of e-shops to make the transshipment economical. However, many factors that influence the effect of transshipment are uncertain and fuzzy, such as customer demand, product price and inventory level. Based on the cloud model theory, a novel method for evaluation of e-shop transshipment selection in the same network shopping mall is proposed to solve the problem. The factors that influence the transshipment effect are discussed in detail. An example of selecting the optimal e-shop to transship products to the out of stock e-shop is given on the basis of the steps of our evaluation calculation. Finally, the result shows that it can effectively optimize transshipment in online shopping economically.展开更多
After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtuali...After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtualization. This study also compares Microsoft, Trend Micro, and the proposed unified cloud computing architecture to show that the proposed unified framework of the cloud computing service model is comprehensive and appropriate for the current complexities of businesses. The findings of this study can contribute to the knowledge for academics and practitioners to understand, assess, and analyze a cloud computing service application.展开更多
A convective cloud transport model, without chemical processes, is developed by joining a set of concentration conservative equations into a two-dimensional, slab-symmetric and fully elastic numerical cloud model, and...A convective cloud transport model, without chemical processes, is developed by joining a set of concentration conservative equations into a two-dimensional, slab-symmetric and fully elastic numerical cloud model, and a numerical experiment is completed to simulate the vertical transport of ground-borne, inert gaseous pollutant by deepthunderstorm. The simulation shows that deep convective storm can very effectively transport high concentrated pollutant gas from PBL upward to the upper troposphere in 30 to 40 minutes, where the pollutant spreads laterally outward with strong anvil outflow, forming an extensive high concentration area. Meanwhile, relatively low concentration areas are formed in PBL both below and beside the cloud, mainly caused by dynamic pumping effect and sub-cloud downdraft flow. About 80% of the pollutant gas transported to the upper troposphere is from the layer below 1.5 km AGL (above ground level).展开更多
The traditional generalization-based knowledge discovery method is introduced. A new kind of multilevel spatial association of the rules mining method based on the cloud model is presented. The cloud model integrates ...The traditional generalization-based knowledge discovery method is introduced. A new kind of multilevel spatial association of the rules mining method based on the cloud model is presented. The cloud model integrates the vague and random use of linguistic terms in a unified way. With these models, spatial and nonspatial attribute values are well generalized at multiple levels, allowing discovery of strong spatial association rules. Combining the cloud model based method with Apriori algorithms for mining association rules from a spatial database shows benefits in being effective and flexible.展开更多
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 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.
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supported by the National Science and Technology Major Project of Water Pollution Control and Treatment(Grants No.2014ZX07405002,2012ZX07506007,2012ZX07506006,and 2012ZX07506002)the Natural Science Foundation of the Anhui Higher Education Institutions of China(Grant No.KJ2016A868)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘With a focus on the difficulty of quantitatively describing the degree of nonuniformity of temporal and spatial distributions of water resources, quantitative research was carried out on the temporal and spatial distribution characteristics of water resources in Guangdong Province from 1956 to 2000 based on a cloud model. The spatial variation of the temporal distribution characteristics and the temporal variation of the spatial distribution characteristics were both analyzed. In addition, the relationships between the numerical characteristics of the cloud model of temporal and spatial distributions of water resources and precipitation were also studied. The results show that, using a cloud model, it is possible to intuitively describe the temporal and spatial distribution characteristics of water resources in cloud images. Water resources in Guangdong Province and their temporal and spatial distribution characteristics are differentiated by their geographic locations. Downstream and coastal areas have a larger amount of water resources with greater uniformity and stronger stability in terms of temporal distribution. Regions with more precipitation possess larger amounts of water resources, and years with more precipitation show greater nonuniformity in the spatial distribution of water resources. The correlation between the nonuniformity of the temporal distribution and local precipitation is small, and no correlation is found between the stability of the nonuniformity of the temporal and spatial distributions of water resources and precipitation. The amount of water resources in Guangdong Province shows an increasing trend from 1956 to 2000, the nonuniformity of the spatial distribution of water resources declines, and the stability of the nonuniformity of the spatial distribution of water resources is enhanced.
文摘The veracity of land evaluation is tightly related to the reasonable weights of land evaluation fac- tors. By mapping qualitative linguistic words into a fine-changeable cloud drops and translating the uncertain factor conditions into quantitative values with the uncertain illation based on cloud model, and then, inte- grating correlation analysis, a new way of figuring out the weight of land evaluation factors is proposed. It may solve the limitations of the conventional ways.
基金supported by the National Natural Science Foundation of China(Grant No.51379162)the Water Conservancy Science and Technology Innovation Project of Guangdong Province(Grant No.2016-06)
文摘Uncertainties existing in the process of dam deformation negatively influence deformation prediction.However,existing deformation pre-diction models seldom consider uncertainties.In this study,a cloud-Verhulst hybrid prediction model was established by combing a cloud model with the Verhulst model.The expectation,one of the cloud characteristic parameters,was obtained using the Verhulst model,and the other two cloud characteristic parameters,entropy and hyper-entropy,were calculated by introducing inertia weight.The hybrid prediction model was used to predict the dam deformation in a hydroelectric project.Comparison of the prediction results of the hybrid prediction model with those of a traditional statistical model and the monitoring values shows that the proposed model has higher prediction accuracy than the traditional sta-tistical model.It provides a new approach to predicting dam deformation under uncertain conditions.
基金Project(2018YFC0808404)supported by National Key Research and Development Program of China。
文摘Ventilation system is significant in underground metal mine of alpine region.Reasonable evaluation of ventilation effectiveness will lead to a practical improvement for the maintenance and management of ventilation system.However,it is difficult to make an effective evaluation of ventilation system due to the lack of classification criteria with respect to underground metal mine in alpine region.This paper proposes a novel evaluation method called the cloud model-clustering analysis(CMCA).Cloud model(CM)is utilized to process collected data of ventilation system,and they are converted into cloud descriptors by CM.Cloud similarity(CS)based Euclidean distance(ED)is proposed to make clustering analysis of assessed samples.Then the classification of assessed samples will be identified by clustering analysis results.A case study is developed based on CMCA.Evaluation results show that ventilation effectiveness can be well classified.Moreover,CM is used alone to make comparison of evaluation results obtained by CMCA.Then the availability and validity of CMCA is verified.Meanwhile,difference of CS based ED and classical ED is analyzed.Two new clustering analysis methods are introduced to make comparison with CMCA.Then the ability of proposed CMCA to meet evaluation requirements of ventilation system is verified.
文摘Time series prediction has been successfully used in several application areas, such as meteoro-logical forecasting, market prediction, network traffic forecasting, etc. , and a number of techniques have been developed for modeling and predicting time series. In the traditional exponential smoothing method, a fixed weight is assigned to data history, and the trend changes of time series are ignored. In this paper, an uncertainty reasoning method, based on cloud model, is employed in time series prediction, which uses cloud logic controller to adjust the smoothing coefficient of the simple exponential smoothing method dynamically to fit the current trend of the time series. The validity of this solution was proved by experiments on various data sets.
基金financially supported by the National Key R&D Program of China(No.2018YFC0831800)the National Natural Science Foundation of China(No.71704178)+3 种基金the Beijing Excellent Talent Program(No.2017000020124G133)the Major Consulting Project of Chinese Academy of Engineering(No.2017-ZD-03)the National Statistical Science Research Project by National Bureau of Statistics of China(No.2017LY10)the Fundamental Research Funds for the Central Universities(No.2020YQNY08)。
文摘Mine closure is associated with many negative impacts on society and the environment.If these effects are not rationally addressed,they would pose risks of mine closure.Thus,a risk management method is needed to mitigate these adverse impacts and address mine-closure issues.An integral framework for mine-closure risk management that includes risk assessment and risk treatment was proposed.Given the fuzziness and randomness of the transformation between qualitative and quantitative knowledge in the risk assessment process,a novel risk assessment method based on the cloud model was presented,which fully considers the uncertainty in risks themselves and in the reasoning process.Closed mine reutilization is an effective risk treatment option in response to the identified high risks,but it requires selecting optimal reutilization strategies for the successful implementation of the reuse plan.To this end,a hybrid semi-quantitative decision method is proposed to optimize decision-making.The results of a case study showed that this risk management methodology can help budget planning for risk treatment and provide an instructional framework to effectively reduce the negative effects of closed mines.
基金supported by the Natural Science Foundation of China(Grant No.51939004)the Fundamental Research Funds for the Central Universities(Grant No.B210204009)the China Huaneng Group Science and Technology Project(Grant No.HNKJ18-H24).
文摘Safety evaluation of toppling rock slopes developing in reservoir areas is crucial. To reduce the uncertainty of safety evaluation, this study developed a composite cloud model, which improved the combination weights of the decision-making trial and evaluation laboratory (DEMATEL) and criteria importance through intercriteria correlation (CRITIC) methods. A safety evaluation system was developed according to in situ monitoring data. The backward cloud generator was used to calculate the numerical characteristics of a cloud model of quantitative indices, and different virtual clouds were used to synthesize some clouds into a generalized one. The synthesized numerical characteristics were calculated to comprehensively evaluate the safety of toppling rock slopes. A case study of a toppling rock slope near the Huangdeng Hydropower Station in China was conducted using monitoring data collected since operation of the hydropower project began. The results indicated that the toppling rock slope was moderately safe with a low safety margin. The composite cloud model considers the fuzziness and randomness of safety evaluation and enables interchange between qualitative and quantitative knowledge. This study provides a new theoretical method for evaluating the safety of toppling rock slopes. It can aid in the predication, control, and even prevention of disasters.
基金supported by the State Grid Corporation of China(KJ21-1-56).
文摘With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.
基金supported by National Natural Science Foundation of China (No.51079033,No.60704004)the Fundamental Research Funds for the Central Universities (No.HEUCFR1009)
文摘In ships having two rudders, an angle error exists if there is a difference in structural and electrical parameters in two steering gear systems. Such an error also results in reduced efficiency of ship maneuverability during navigation. For the sake of reducing the angle error, a synchro-ballistic control approach based on cloud model is proposed in this paper. First, the mechanism model of steering gear system is introduced. Second, the structure of synchro-control system of twin-rudder is proposed based on the master-slave control strategy. Third, synchro-ballistic controller based on cloud model is designed to solve the nonlinearity and uncertainty of system. Finally, the designed controller is tested via simulation under two different situations. The simulated results demonstrate that this method is simple and has stronger robustness against the variation of states and parameters of plants. Hence, the validity and reliability of the method is proved for synchro-control of two rudders, which is a significant engineering application.
基金the Zhejiang Province Natural Science Foundation of China(No.LQ15G010007)the Zhejiang Province Postdoctoral Foundation of China(No.BSH1402043)
文摘In e-commerce, a critical problem is how to transship the products between different e-shops to lessen the risk of out of stock, especially in network shopping mall of China. Most of importance is how to select the optimal one in the waiting list of e-shops to make the transshipment economical. However, many factors that influence the effect of transshipment are uncertain and fuzzy, such as customer demand, product price and inventory level. Based on the cloud model theory, a novel method for evaluation of e-shop transshipment selection in the same network shopping mall is proposed to solve the problem. The factors that influence the transshipment effect are discussed in detail. An example of selecting the optimal e-shop to transship products to the out of stock e-shop is given on the basis of the steps of our evaluation calculation. Finally, the result shows that it can effectively optimize transshipment in online shopping economically.
文摘After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtualization. This study also compares Microsoft, Trend Micro, and the proposed unified cloud computing architecture to show that the proposed unified framework of the cloud computing service model is comprehensive and appropriate for the current complexities of businesses. The findings of this study can contribute to the knowledge for academics and practitioners to understand, assess, and analyze a cloud computing service application.
基金This Project is supported by the National Natural Science Foundation of China.
文摘A convective cloud transport model, without chemical processes, is developed by joining a set of concentration conservative equations into a two-dimensional, slab-symmetric and fully elastic numerical cloud model, and a numerical experiment is completed to simulate the vertical transport of ground-borne, inert gaseous pollutant by deepthunderstorm. The simulation shows that deep convective storm can very effectively transport high concentrated pollutant gas from PBL upward to the upper troposphere in 30 to 40 minutes, where the pollutant spreads laterally outward with strong anvil outflow, forming an extensive high concentration area. Meanwhile, relatively low concentration areas are formed in PBL both below and beside the cloud, mainly caused by dynamic pumping effect and sub-cloud downdraft flow. About 80% of the pollutant gas transported to the upper troposphere is from the layer below 1.5 km AGL (above ground level).
文摘The traditional generalization-based knowledge discovery method is introduced. A new kind of multilevel spatial association of the rules mining method based on the cloud model is presented. The cloud model integrates the vague and random use of linguistic terms in a unified way. With these models, spatial and nonspatial attribute values are well generalized at multiple levels, allowing discovery of strong spatial association rules. Combining the cloud model based method with Apriori algorithms for mining association rules from a spatial database shows benefits in being effective and flexible.
