Selecting the optimum location with attention to conditions and restrictions is one of the most importantfactors in establishing a manufacturing plant. Identification of effective criteria is an important stage in the...Selecting the optimum location with attention to conditions and restrictions is one of the most importantfactors in establishing a manufacturing plant. Identification of effective criteria is an important stage in the selection for the location of industrial units. In this study, an analytic hierarchy process （AHP） was applied to select the most effective criteria for the location of MDF （medium density fiberboard） industry in Mazandaran Province, Iran. A consideration in ttaining this goal is that Mazandaran is favored over other provinces because of its resources of raw lignocellulosic ma- erial required for wood and paper industries. The results indicate that the criterion of ＂materials and products＂ and the ub-criterion of ＂reliability of supply of raw material＂ are the most important factors.展开更多
In China, farmers employed in non-farm work have become important socio-economic actors, but few studies have examined the farmers' perspective in making their work location choices. Based on "push-pull"...In China, farmers employed in non-farm work have become important socio-economic actors, but few studies have examined the farmers' perspective in making their work location choices. Based on "push-pull" migration theory, this paper utilizes sectional data from a 2013 survey of farmers in China's Three Gorges Reservoir area to empirically analyze the factors influencing migrant workers' choice of employment location. The results indicate that 60.46% of laborers have migrated from their home province, whereas 39.54% have remained in their home province. Focusing on personal, household, and community characteristics—in addition to the economic characteristics of the sample counties—multinomial logistic regression models reveal that farmer-laborers' employment location decisions are influenced by their personal capital endowment(age, years of education and social networks), family structure(the number of laborers, elders, children and students), home village characteristics(location, economic development level and the degree of relief of the land) and home county economic development level. Notably, male and female laborers' location decisions reveal a converging trend, and their differences are not pronounced. Per capita arable land area has little influence on location decisions, whereas the educational level of laborers has a significant impact. The results differ significantly from those found in previous studies.展开更多
Although there are many papers on variable selection methods based on mean model in the nite mixture of regression models,little work has been done on how to select signi cant explanatory variables in the modeling of ...Although there are many papers on variable selection methods based on mean model in the nite mixture of regression models,little work has been done on how to select signi cant explanatory variables in the modeling of the variance parameter.In this paper,we propose and study a novel class of models:a skew-normal mixture of joint location and scale models to analyze the heteroscedastic skew-normal data coming from a heterogeneous population.The problem of variable selection for the proposed models is considered.In particular,a modi ed Expectation-Maximization(EM)algorithm for estimating the model parameters is developed.The consistency and the oracle property of the penalized estimators is established.Simulation studies are conducted to investigate the nite sample performance of the proposed methodolo-gies.An example is illustrated by the proposed methodologies.展开更多
The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications direct...The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications directly addressing the research problem at hand.Similarly,while the body of work on optimal location and sizing of renewable energy generators(REGs)in balanced distribution systems is substantial,only the most pertinent sources are cited,aligning closely with the study’s objective function.A comprehensive literature review reveals several key research areas:RES integration,RES-related optimization techniques,strategic placement of wind and solar generation,and RES promotion in deregulated powermarkets,particularly within transmission systems.Furthermore,the optimal location and sizing of REGs in both balanced and unbalanced distribution systems have been extensively studied.RESs demonstrate significant potential for standalone applications in remote areas lacking conventional transmission and distribution infrastructure.Also presents a thorough review of current modeling and optimization approaches for RES-based distribution system location and sizing.Additionally,it examines the optimal positioning,sizing,and performance of hybrid and standalone renewable energy systems.This paper provides a comprehensive review of current modeling and optimization approaches for the location and sizing of Renewable Energy Sources(RESs)in distribution systems,focusing on both balanced and unbalanced networks.展开更多
选址问题是任何一个商业机构都要面临的重大决策问题之一,它受多种因素制约,比如社会经济学、地质学、生态学以及决策者的特定需求等。现有的选址方法(通常被经济学家采用)大多利用主观评价,可扩展性差。空间co-location模式挖掘是空间...选址问题是任何一个商业机构都要面临的重大决策问题之一,它受多种因素制约,比如社会经济学、地质学、生态学以及决策者的特定需求等。现有的选址方法(通常被经济学家采用)大多利用主观评价,可扩展性差。空间co-location模式挖掘是空间数据挖掘的一个重要研究方向。一个频繁co-location模式是一组空间特征的子集,它们的实例在空间中频繁关联。利用co-location模式的这种特征间"共存"关系,提出了一种基于co-location模式的地址选择算法,该算法基于本体描述空间数据的分类信息,并在本体的指导下对用户感兴趣的兴趣点(Point of Interest)进行关键co-location模式挖掘,同时针对实际情况对数据进行了预处理以增加算法的有效性。在真实数据集(北京市的兴趣点数据)上的评估实验显示该算法具有较高的准确率,选择的地址具有高可靠性。展开更多
Locating distribution centers optimally is a crucial and systematic task for decision-makers.Optimally located distribution centers can significantly improve the logistics system's efficiency and reduce its operat...Locating distribution centers optimally is a crucial and systematic task for decision-makers.Optimally located distribution centers can significantly improve the logistics system's efficiency and reduce its operational costs.However,it is not an easy task to optimize distribution center locations and previous studies focused primarily on location optimization of a single distribution center.With growing logistics demands,multiple distribution centers become necessary to meet customers' requirements,but few studies have tackled the multiple distribution center locations(MDCLs) problem.This paper presents a comprehensive algorithm to address the MDCLs problem.Fuzzy integration and clustering approach using the improved axiomatic fuzzy set(AFS) theory is developed for location clustering based on multiple hierarchical evaluation criteria.Then,technique for order preference by similarity to ideal solution(TOPSIS) is applied for evaluating and selecting the best candidate for each cluster.Sensitivity analysis is also conducted to assess the influence of each criterion in the location planning decision procedure.Results from a case study in Guiyang,China,reveals that the proposed approach developed in this study outperforms other similar algorithms for MDCLs selection.This new method may easily be extended to address location planning of other types of facilities,including hospitals,fire stations and schools.展开更多
This article presents a comprehensive framework for determining the location of road weather information system （RWIS） stations over a regional road network. In the proposed methodology, the region is divided into a...This article presents a comprehensive framework for determining the location of road weather information system （RWIS） stations over a regional road network. In the proposed methodology, the region is divided into a grid of equal-sized zones which are considered as the minimum spatial unit for allocating a candidate set of RWIS stations. These zones are ranked according to a set of pre-specified criteria that reflect the needs for, and potential benefits from, real-time RWIS, including road surface temperature variability, precipitation, network traffic, and collision patterns. A case study based on the existing RWIS network in the province of Ontario was conducted to illustrate the major features of the proposed method and evaluate the implications of alternative loca- tion selection criteria. The findings of the study suggest that it is feasible to develop a systematic process for locating RWIS stations using an integrated location criterion to capture multiple factors being considered in prac- tice. The study has also revealed the need to establish quantitative models for estimating the benefit of real-time information from RWIS stations, which is the foundation of a cost-benefit-based RWIS location optimization model.展开更多
The location pattern of different commercial stores in Shichahai, a historic conservation area in Beijing, was investigated from a street centrality perspective. Many previous studies have investigated the relationshi...The location pattern of different commercial stores in Shichahai, a historic conservation area in Beijing, was investigated from a street centrality perspective. Many previous studies have investigated the relationship between street centrality and land use patterns or commercial activities at interurban or intraurban scales. We considered Shichahai in this study to determine if street centrality applied at the street scale and if the street network was the only factor influencing the selection of store location. First, the nearest neighbor index, nearest neighbor hierarchical spatial cluster(NNHSC), and kernel density estimation(KDE) methods were used to provide baseline spatial distributions of commercial stores. Second, urban network analysis(UNA) tools were used to measure the street centrality indices under two conditions, with and without the weighting of cultural relics calculated by a principal component analysis(PCA). Finally, both store locations and centrality values at nodes were transformed to one unit(raster pixel) for a correlation analysis.The results showed that three of the four store types were clustered and had their own hotspots that were mostly located in the eastern and central parts of city blocks. The most momentous findings were determined from the street centrality indices. Among the three store types with correlation coefficients above 0.5, all centrality indices with landmark weighting, except straightness, had higher correlations,with closeness with landmark weighting having the highest correlation, followed by betweenness with landmark weighting. Therefore,we statistically concluded that street centrality could apply at the street scale and that the street network was not the only factor that influenced store location pattern, with landmarks also playing a significant role. The results provide guidance in determining the selection strategy for stores in a historic conservation area.展开更多
Based on the characteristics of the air alliance environment saving transport mileage,the hub location problem of the air cargo network was studied.First,the air alliance selection probability model was introduced to ...Based on the characteristics of the air alliance environment saving transport mileage,the hub location problem of the air cargo network was studied.First,the air alliance selection probability model was introduced to determine the alliance self-operation or outsourcing probability in different segments.Then,according to the location center rule,with the goal of minimizing the total cost,the hub location model was built.The improved immune chaos genetic algorithm was used to solve this model.The results show that the improved algorithm has stronger convergence and better effect than the immune genetic algorithm.When the number of hubs increases,the fixed cost increases,but the transportation cost decreases.The greater the discount factor,the fixed cost,and the self operating cost sharing coefficient,the higher the total network cost.The airline which joins the air alliance can greatly reduce the operating cost of airlines.Therefore,airlines should consider joining the alliance.展开更多
As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of ...As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of EVs.In other words,reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system.Considering the construction and maintenance of the charging station,the distribution network loss of the charging station,and the economic loss on the user side of the EV,this paper takes the node and capacity of charging station planning as control variables and the minimum cost of system comprehensive planning as objective function,and thus proposes a location and capacity planning model for the EV charging station.Based on the problems of low efficiency and insufficient global optimization ability of the current algorithm,the simulated annealing immune particle swarm optimization algorithm(SA-IPSO)is adopted in this paper.The simulated annealing algorithm is used in the global update of the particle swarm optimization(PSO),and the immune mechanism is introduced to participate in the iterative update of the particles,so as to improve the speed and efficiency of PSO.Voronoi diagram is used to divide service area of the charging station,and a joint solution process of Voronoi diagram and SA-IPSO is proposed.By example analysis,the results show that the optimal solution corresponding to the optimisation method proposed in this paper has a low overall cost,while the average charging waiting time is only 1.8 min and the charging pile utilisation rate is 75.5%.The simulation comparison verifies that the improved algorithm improves the operational efficiency by 18.1%and basically does not fall into local convergence.展开更多
Due to the lack of consideration of movement behavior information other than time and location perception in current location prediction methods,the movement characteristics of trajectory data cannot be well expressed...Due to the lack of consideration of movement behavior information other than time and location perception in current location prediction methods,the movement characteristics of trajectory data cannot be well expressed,which in turn affects the accuracy of the prediction results.First,a new trajectory data expression method by associating the movement behavior information is given.The pre-association method is used to model the movement behavior information according to the individual movement behavior features and the group movement behavior features extracted from the trajectory sequence and the region.The movement behavior features based on pre-association may not always be the best for the prediction model.Therefore,through association analysis and importance analysis,the final association feature is selected from the pre-association features.The trajectory data is input into the LSTM networks after associated features and genetic algorithm(GA)is used to optimize the combination of the length of time window and the number of hidden layer nodes.The experimental results show that compared with the original trajectory data,the trajectory data associated with the movement behavior information helps to improve the accuracy of location prediction.展开更多
Differentiation of syndromes can be done by three steps:First to differentiate thenature of disease,second to differentiate the location of disease,third to analyse comprehensively thenature and location of disease.De...Differentiation of syndromes can be done by three steps:First to differentiate thenature of disease,second to differentiate the location of disease,third to analyse comprehensively thenature and location of disease.Depend on complete differentiation of syndromes,the acupoints are selected.Three cases are analysed to explain how to dominate preceding contents.展开更多
To expedite the large-scale deployment of driverless taxis and advance the autonomous driving industry,research on the location of integrated parking and charging facilities for driverless taxis has emerged as a signi...To expedite the large-scale deployment of driverless taxis and advance the autonomous driving industry,research on the location of integrated parking and charging facilities for driverless taxis has emerged as a significant issue in urban traffic.This study employs a progressive"preliminary selection-screening-optimal selection"approach for site selec-tion.First,the preliminary selection of parking sites is conducted by clustering various point-of-interest types.Subsequently,a multi-objective site selection model is developed to maximize the coverage of demand points,minimize construction costs,address the lar-gest population demands,and minimize the distance between demand points and candi-date sites.The non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ)is adopted to obtain several Pareto optimal solutions.The evaluation indexes are selected according to opera-tors,users,and the public transport system to estimate the Pareto optimal solutions,and then the final location solution can be obtained.The calculation methods for several key parameters are improved during the modeling process.Location potential and location influence coefficient are selected to adjust the number of driverless taxi parking spaces.Additionally,isochrones drawn based on the actual road network and path planning repre-sent the service range of candidate points.Meanwhile,distance based on actual road net-work rather than Euclidean distance is introduced to calculate the distance between candidate points.Finally,a case study shows that the method proposed in this study could reduce the total initial travel time to reach the demand points by 64%,which is indepen-dent of operational scheduling.展开更多
文摘Selecting the optimum location with attention to conditions and restrictions is one of the most importantfactors in establishing a manufacturing plant. Identification of effective criteria is an important stage in the selection for the location of industrial units. In this study, an analytic hierarchy process （AHP） was applied to select the most effective criteria for the location of MDF （medium density fiberboard） industry in Mazandaran Province, Iran. A consideration in ttaining this goal is that Mazandaran is favored over other provinces because of its resources of raw lignocellulosic ma- erial required for wood and paper industries. The results indicate that the criterion of ＂materials and products＂ and the ub-criterion of ＂reliability of supply of raw material＂ are the most important factors.
基金financial supports from the National Natural Science Foundation of China (Grant Nos. 41571527, 41301193, 41101552,41401198)Main Direction Program (KZCX2-EW317)West Light Foundation of the Chinese Academy of Sciences (2013Yuhui)
文摘In China, farmers employed in non-farm work have become important socio-economic actors, but few studies have examined the farmers' perspective in making their work location choices. Based on "push-pull" migration theory, this paper utilizes sectional data from a 2013 survey of farmers in China's Three Gorges Reservoir area to empirically analyze the factors influencing migrant workers' choice of employment location. The results indicate that 60.46% of laborers have migrated from their home province, whereas 39.54% have remained in their home province. Focusing on personal, household, and community characteristics—in addition to the economic characteristics of the sample counties—multinomial logistic regression models reveal that farmer-laborers' employment location decisions are influenced by their personal capital endowment(age, years of education and social networks), family structure(the number of laborers, elders, children and students), home village characteristics(location, economic development level and the degree of relief of the land) and home county economic development level. Notably, male and female laborers' location decisions reveal a converging trend, and their differences are not pronounced. Per capita arable land area has little influence on location decisions, whereas the educational level of laborers has a significant impact. The results differ significantly from those found in previous studies.
基金Supported by the National Natural Science Foundation of China(11861041).
文摘Although there are many papers on variable selection methods based on mean model in the nite mixture of regression models,little work has been done on how to select signi cant explanatory variables in the modeling of the variance parameter.In this paper,we propose and study a novel class of models:a skew-normal mixture of joint location and scale models to analyze the heteroscedastic skew-normal data coming from a heterogeneous population.The problem of variable selection for the proposed models is considered.In particular,a modi ed Expectation-Maximization(EM)algorithm for estimating the model parameters is developed.The consistency and the oracle property of the penalized estimators is established.Simulation studies are conducted to investigate the nite sample performance of the proposed methodolo-gies.An example is illustrated by the proposed methodologies.
文摘The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications directly addressing the research problem at hand.Similarly,while the body of work on optimal location and sizing of renewable energy generators(REGs)in balanced distribution systems is substantial,only the most pertinent sources are cited,aligning closely with the study’s objective function.A comprehensive literature review reveals several key research areas:RES integration,RES-related optimization techniques,strategic placement of wind and solar generation,and RES promotion in deregulated powermarkets,particularly within transmission systems.Furthermore,the optimal location and sizing of REGs in both balanced and unbalanced distribution systems have been extensively studied.RESs demonstrate significant potential for standalone applications in remote areas lacking conventional transmission and distribution infrastructure.Also presents a thorough review of current modeling and optimization approaches for RES-based distribution system location and sizing.Additionally,it examines the optimal positioning,sizing,and performance of hybrid and standalone renewable energy systems.This paper provides a comprehensive review of current modeling and optimization approaches for the location and sizing of Renewable Energy Sources(RESs)in distribution systems,focusing on both balanced and unbalanced networks.
文摘选址问题是任何一个商业机构都要面临的重大决策问题之一,它受多种因素制约,比如社会经济学、地质学、生态学以及决策者的特定需求等。现有的选址方法(通常被经济学家采用)大多利用主观评价,可扩展性差。空间co-location模式挖掘是空间数据挖掘的一个重要研究方向。一个频繁co-location模式是一组空间特征的子集,它们的实例在空间中频繁关联。利用co-location模式的这种特征间"共存"关系,提出了一种基于co-location模式的地址选择算法,该算法基于本体描述空间数据的分类信息,并在本体的指导下对用户感兴趣的兴趣点(Point of Interest)进行关键co-location模式挖掘,同时针对实际情况对数据进行了预处理以增加算法的有效性。在真实数据集(北京市的兴趣点数据)上的评估实验显示该算法具有较高的准确率,选择的地址具有高可靠性。
基金Project supported by the National Natural Science Foundation of China (Nos. 51028802 and 70902029)the PhD Programs Foundation of Ministry of Education of China (No. 20090092120045)
文摘Locating distribution centers optimally is a crucial and systematic task for decision-makers.Optimally located distribution centers can significantly improve the logistics system's efficiency and reduce its operational costs.However,it is not an easy task to optimize distribution center locations and previous studies focused primarily on location optimization of a single distribution center.With growing logistics demands,multiple distribution centers become necessary to meet customers' requirements,but few studies have tackled the multiple distribution center locations(MDCLs) problem.This paper presents a comprehensive algorithm to address the MDCLs problem.Fuzzy integration and clustering approach using the improved axiomatic fuzzy set(AFS) theory is developed for location clustering based on multiple hierarchical evaluation criteria.Then,technique for order preference by similarity to ideal solution(TOPSIS) is applied for evaluating and selecting the best candidate for each cluster.Sensitivity analysis is also conducted to assess the influence of each criterion in the location planning decision procedure.Results from a case study in Guiyang,China,reveals that the proposed approach developed in this study outperforms other similar algorithms for MDCLs selection.This new method may easily be extended to address location planning of other types of facilities,including hospitals,fire stations and schools.
基金funded by the Aurora Programfunded by National Sciences and Engineering Research Council of Canada (NSERC)Ontario Ministry of Transportation (MTO)
文摘This article presents a comprehensive framework for determining the location of road weather information system （RWIS） stations over a regional road network. In the proposed methodology, the region is divided into a grid of equal-sized zones which are considered as the minimum spatial unit for allocating a candidate set of RWIS stations. These zones are ranked according to a set of pre-specified criteria that reflect the needs for, and potential benefits from, real-time RWIS, including road surface temperature variability, precipitation, network traffic, and collision patterns. A case study based on the existing RWIS network in the province of Ontario was conducted to illustrate the major features of the proposed method and evaluate the implications of alternative loca- tion selection criteria. The findings of the study suggest that it is feasible to develop a systematic process for locating RWIS stations using an integrated location criterion to capture multiple factors being considered in prac- tice. The study has also revealed the need to establish quantitative models for estimating the benefit of real-time information from RWIS stations, which is the foundation of a cost-benefit-based RWIS location optimization model.
基金Under the auspices of National Natural Science Foundation of China(No.51478007,51178016)Project of Fundamental Research of Chinese Cultural Heritage Research Institute(No.2016-JBKY-08)
文摘The location pattern of different commercial stores in Shichahai, a historic conservation area in Beijing, was investigated from a street centrality perspective. Many previous studies have investigated the relationship between street centrality and land use patterns or commercial activities at interurban or intraurban scales. We considered Shichahai in this study to determine if street centrality applied at the street scale and if the street network was the only factor influencing the selection of store location. First, the nearest neighbor index, nearest neighbor hierarchical spatial cluster(NNHSC), and kernel density estimation(KDE) methods were used to provide baseline spatial distributions of commercial stores. Second, urban network analysis(UNA) tools were used to measure the street centrality indices under two conditions, with and without the weighting of cultural relics calculated by a principal component analysis(PCA). Finally, both store locations and centrality values at nodes were transformed to one unit(raster pixel) for a correlation analysis.The results showed that three of the four store types were clustered and had their own hotspots that were mostly located in the eastern and central parts of city blocks. The most momentous findings were determined from the street centrality indices. Among the three store types with correlation coefficients above 0.5, all centrality indices with landmark weighting, except straightness, had higher correlations,with closeness with landmark weighting having the highest correlation, followed by betweenness with landmark weighting. Therefore,we statistically concluded that street centrality could apply at the street scale and that the street network was not the only factor that influenced store location pattern, with landmarks also playing a significant role. The results provide guidance in determining the selection strategy for stores in a historic conservation area.
基金The National Social Science Foundation of China(No.17XGL013)。
文摘Based on the characteristics of the air alliance environment saving transport mileage,the hub location problem of the air cargo network was studied.First,the air alliance selection probability model was introduced to determine the alliance self-operation or outsourcing probability in different segments.Then,according to the location center rule,with the goal of minimizing the total cost,the hub location model was built.The improved immune chaos genetic algorithm was used to solve this model.The results show that the improved algorithm has stronger convergence and better effect than the immune genetic algorithm.When the number of hubs increases,the fixed cost increases,but the transportation cost decreases.The greater the discount factor,the fixed cost,and the self operating cost sharing coefficient,the higher the total network cost.The airline which joins the air alliance can greatly reduce the operating cost of airlines.Therefore,airlines should consider joining the alliance.
基金Key R&D Program of Tianjin,China(No.20YFYSGX00060).
文摘As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of EVs.In other words,reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system.Considering the construction and maintenance of the charging station,the distribution network loss of the charging station,and the economic loss on the user side of the EV,this paper takes the node and capacity of charging station planning as control variables and the minimum cost of system comprehensive planning as objective function,and thus proposes a location and capacity planning model for the EV charging station.Based on the problems of low efficiency and insufficient global optimization ability of the current algorithm,the simulated annealing immune particle swarm optimization algorithm(SA-IPSO)is adopted in this paper.The simulated annealing algorithm is used in the global update of the particle swarm optimization(PSO),and the immune mechanism is introduced to participate in the iterative update of the particles,so as to improve the speed and efficiency of PSO.Voronoi diagram is used to divide service area of the charging station,and a joint solution process of Voronoi diagram and SA-IPSO is proposed.By example analysis,the results show that the optimal solution corresponding to the optimisation method proposed in this paper has a low overall cost,while the average charging waiting time is only 1.8 min and the charging pile utilisation rate is 75.5%.The simulation comparison verifies that the improved algorithm improves the operational efficiency by 18.1%and basically does not fall into local convergence.
基金supported by the Hunan University of Science and Technology Doctoral Research Foundation Project(E51873).
文摘Due to the lack of consideration of movement behavior information other than time and location perception in current location prediction methods,the movement characteristics of trajectory data cannot be well expressed,which in turn affects the accuracy of the prediction results.First,a new trajectory data expression method by associating the movement behavior information is given.The pre-association method is used to model the movement behavior information according to the individual movement behavior features and the group movement behavior features extracted from the trajectory sequence and the region.The movement behavior features based on pre-association may not always be the best for the prediction model.Therefore,through association analysis and importance analysis,the final association feature is selected from the pre-association features.The trajectory data is input into the LSTM networks after associated features and genetic algorithm(GA)is used to optimize the combination of the length of time window and the number of hidden layer nodes.The experimental results show that compared with the original trajectory data,the trajectory data associated with the movement behavior information helps to improve the accuracy of location prediction.
文摘Differentiation of syndromes can be done by three steps:First to differentiate thenature of disease,second to differentiate the location of disease,third to analyse comprehensively thenature and location of disease.Depend on complete differentiation of syndromes,the acupoints are selected.Three cases are analysed to explain how to dominate preceding contents.
基金supported by the Natural Science Foundation of Hubei Province(No.2024AFB826)the National Natural Science Foundation of China(No.52472329)the Research Project of Philosophy and Social Sciences of Hubei Provincial Education Department(No.22Y030).
文摘To expedite the large-scale deployment of driverless taxis and advance the autonomous driving industry,research on the location of integrated parking and charging facilities for driverless taxis has emerged as a significant issue in urban traffic.This study employs a progressive"preliminary selection-screening-optimal selection"approach for site selec-tion.First,the preliminary selection of parking sites is conducted by clustering various point-of-interest types.Subsequently,a multi-objective site selection model is developed to maximize the coverage of demand points,minimize construction costs,address the lar-gest population demands,and minimize the distance between demand points and candi-date sites.The non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ)is adopted to obtain several Pareto optimal solutions.The evaluation indexes are selected according to opera-tors,users,and the public transport system to estimate the Pareto optimal solutions,and then the final location solution can be obtained.The calculation methods for several key parameters are improved during the modeling process.Location potential and location influence coefficient are selected to adjust the number of driverless taxi parking spaces.Additionally,isochrones drawn based on the actual road network and path planning repre-sent the service range of candidate points.Meanwhile,distance based on actual road net-work rather than Euclidean distance is introduced to calculate the distance between candidate points.Finally,a case study shows that the method proposed in this study could reduce the total initial travel time to reach the demand points by 64%,which is indepen-dent of operational scheduling.
