Quality of life(QOL) is a hotspot issue that has attracted increasing attention from the Chinese Government and scholars, it is also a vital issue that should be addressed during the cause of ′establishing overall we...Quality of life(QOL) is a hotspot issue that has attracted increasing attention from the Chinese Government and scholars, it is also a vital issue that should be addressed during the cause of ′establishing overall well-off society′. Northeast China is one of the most import old industrial bases in China, however, the industrial structure of heavy chemical industry and the development mode of ′production first, living last′ have leaded to series of social problems, which have also become a serious bottleneck to social stability and economic sustainable development. Through applying the methods of BP neural network, exploratory spatial data analysis(ESDA) and spatial regression model, this paper examines the space-time dynamics of QOL of the residents in Northeast China. We first investigate the indexes of QOL of the residents and then use ESDA methods to visualize its space-time relationship. We have found a spatial agglomeration of QOL of the residents in middle-southern Liaoning Province, central Jilin Province and Harbin-Qiqihar-Daqing area of Heilongjiang Province. Two third of the counties are low-low spatial correlation, and the correlative type of about 60% of the prefecture level areas keeps stable, indicating QOL of the residents in Northeast China shows a certain character of path dependence or spatial locked. We have also found that economic strength and development levels of service industry have positive and obvious effect on QOL of the residents, while the effect of such indexes as the social service level and the proportion of the tertiary industries are less.展开更多
In this study, a Multi-Layer BP neural network(MLBP) with dynamic thresholds is employed to build a classifier model.As to the design of the neural network structure, theoretical guidance and plentiful experiments are...In this study, a Multi-Layer BP neural network(MLBP) with dynamic thresholds is employed to build a classifier model.As to the design of the neural network structure, theoretical guidance and plentiful experiments are combined to optimize the hidden layers' parameters which include the number of hidden layers and their node numbers.The classifier with dynamic thresholds is used to standardize the output for the first time, and it improves the robustness of the model to a high level.Finally, the classifier is applied to forecast box office revenue of a movie before its theatrical release.The comparison results with the MLP method show that the MLBP classifier model achieves more satisfactory results, and it is more reliable and effective to solve the problem.展开更多
基金Under the auspices of Key Research Program of Chinese Academic of Science(No.KZZD-EW-06-03,KSZD-EW-Z-021-03)Advantage Discipline Project of Hainan Normal University(No.305010048)+2 种基金Key Discipline Project of Hainan(No.3050107048)National Natural Science Foundation of China(No.41201160,41329001)Natural Science Foundation of Hainan Province(No.414189)
文摘Quality of life(QOL) is a hotspot issue that has attracted increasing attention from the Chinese Government and scholars, it is also a vital issue that should be addressed during the cause of ′establishing overall well-off society′. Northeast China is one of the most import old industrial bases in China, however, the industrial structure of heavy chemical industry and the development mode of ′production first, living last′ have leaded to series of social problems, which have also become a serious bottleneck to social stability and economic sustainable development. Through applying the methods of BP neural network, exploratory spatial data analysis(ESDA) and spatial regression model, this paper examines the space-time dynamics of QOL of the residents in Northeast China. We first investigate the indexes of QOL of the residents and then use ESDA methods to visualize its space-time relationship. We have found a spatial agglomeration of QOL of the residents in middle-southern Liaoning Province, central Jilin Province and Harbin-Qiqihar-Daqing area of Heilongjiang Province. Two third of the counties are low-low spatial correlation, and the correlative type of about 60% of the prefecture level areas keeps stable, indicating QOL of the residents in Northeast China shows a certain character of path dependence or spatial locked. We have also found that economic strength and development levels of service industry have positive and obvious effect on QOL of the residents, while the effect of such indexes as the social service level and the proportion of the tertiary industries are less.
基金Supported by National Natural Science Foundation of China (No. 60573172)
文摘In this study, a Multi-Layer BP neural network(MLBP) with dynamic thresholds is employed to build a classifier model.As to the design of the neural network structure, theoretical guidance and plentiful experiments are combined to optimize the hidden layers' parameters which include the number of hidden layers and their node numbers.The classifier with dynamic thresholds is used to standardize the output for the first time, and it improves the robustness of the model to a high level.Finally, the classifier is applied to forecast box office revenue of a movie before its theatrical release.The comparison results with the MLP method show that the MLBP classifier model achieves more satisfactory results, and it is more reliable and effective to solve the problem.
