Modeling and Simulation Technology has become an important means to study various complex systems with its extensive application.Thus,the accuracy of the simulation models becomes a critical problem and needs to be as...Modeling and Simulation Technology has become an important means to study various complex systems with its extensive application.Thus,the accuracy of the simulation models becomes a critical problem and needs to be assessed by employing an appropri-ate model validation method.The simulation models often have multivariate dynamic responses with uncertainty,while most of the existing validation methods concentrate on the validation of the static responses.Hence,a new validation method is proposed in this paper to validate the dynamic responses of the simulation models over the time domain at a single validation site and multiple validation sites through introducing the discrete Chebyshev polynomials and area metric.For each time series,the orthogonal expan-sion coefficients are extracted primarily by representing the time series with the discrete orthogonal polynomials.Then,the area metric and the u-pooling metric are employed to validate all the uncorrelated coefficients at a single validation site and multiple vali-dation sites,respectively,and the final validation result is obtained by summarizing the metric values.The feasibility and effectiveness of the proposed model validation method are illustrated through the example of the terminal guidance stage of the flight vehicle.展开更多
Road network is a corridor system that interacts with surrounding landscapes,and understanding their interaction helps to develop an optimal plan for sustainable transportation and land use.This study investigates the...Road network is a corridor system that interacts with surrounding landscapes,and understanding their interaction helps to develop an optimal plan for sustainable transportation and land use.This study investigates the relationships between road centrality and landscape patterns in the Wuhan Metropolitan Area,China.The densities of centrality measures,including closeness,betweenness,and straightness,are calculated by kernel density estimation(KDE).The landscape patterns are characterized by four landscape metrics,including percentage of landscape(PLAND),Shannon′s diversity index(SHDI),mean patch size(MPS),and mean shape index(MSI).Spearman rank correlation analysis is then used to quantify their relationships at both landscape and class levels.The results show that the centrality measures can reflect the hierarchy of road network as they associate with road grade.Further analysis exhibit that as centrality densities increase,the whole landscape becomes more fragmented and regular.At the class level,the forest gradually decreases and becomes fragmented,while the construction land increases and turns to more compact.Therefore,these findings indicate that the ability and potential applications of centrality densities estimated by KDE in quantifying the relationships between roads and landscapes,can provide detailed information and valuable guidance for transportation and land-use planning as well as a new insight into ecological effects of roads.展开更多
基金The research is supported by National Key R&D Program of China(Grant No.2018YFB1701600).
文摘Modeling and Simulation Technology has become an important means to study various complex systems with its extensive application.Thus,the accuracy of the simulation models becomes a critical problem and needs to be assessed by employing an appropri-ate model validation method.The simulation models often have multivariate dynamic responses with uncertainty,while most of the existing validation methods concentrate on the validation of the static responses.Hence,a new validation method is proposed in this paper to validate the dynamic responses of the simulation models over the time domain at a single validation site and multiple validation sites through introducing the discrete Chebyshev polynomials and area metric.For each time series,the orthogonal expan-sion coefficients are extracted primarily by representing the time series with the discrete orthogonal polynomials.Then,the area metric and the u-pooling metric are employed to validate all the uncorrelated coefficients at a single validation site and multiple vali-dation sites,respectively,and the final validation result is obtained by summarizing the metric values.The feasibility and effectiveness of the proposed model validation method are illustrated through the example of the terminal guidance stage of the flight vehicle.
基金Under the auspices of National Key Technology Research and Development Program of China(No.2012BAH28B02)
文摘Road network is a corridor system that interacts with surrounding landscapes,and understanding their interaction helps to develop an optimal plan for sustainable transportation and land use.This study investigates the relationships between road centrality and landscape patterns in the Wuhan Metropolitan Area,China.The densities of centrality measures,including closeness,betweenness,and straightness,are calculated by kernel density estimation(KDE).The landscape patterns are characterized by four landscape metrics,including percentage of landscape(PLAND),Shannon′s diversity index(SHDI),mean patch size(MPS),and mean shape index(MSI).Spearman rank correlation analysis is then used to quantify their relationships at both landscape and class levels.The results show that the centrality measures can reflect the hierarchy of road network as they associate with road grade.Further analysis exhibit that as centrality densities increase,the whole landscape becomes more fragmented and regular.At the class level,the forest gradually decreases and becomes fragmented,while the construction land increases and turns to more compact.Therefore,these findings indicate that the ability and potential applications of centrality densities estimated by KDE in quantifying the relationships between roads and landscapes,can provide detailed information and valuable guidance for transportation and land-use planning as well as a new insight into ecological effects of roads.
