[Objective] The aim was to establish Elman neural network model to predict the dynamic changes of temperature. [Method] Considering the inherent nature of temperature, and dy dint of the temperature in Chongqing durin...[Objective] The aim was to establish Elman neural network model to predict the dynamic changes of temperature. [Method] Considering the inherent nature of temperature, and dy dint of the temperature in Chongqing during 1951-2010, the Elman artificial neural network model was applied to predict the temperature. [Result] This simulation result suggested that the relative error was small and can have a good simulation to the future temperature changes. [Conclusion] The prediction result can guide agricultural production and further apply to the field of pricing the weather derivative products.展开更多
Based on the research on the rural living standard in China in terms of annual net income per capita, we de-fine six types of village-level economy, i.e. "to be extremely poor", "to make a basic living&...Based on the research on the rural living standard in China in terms of annual net income per capita, we de-fine six types of village-level economy, i.e. "to be extremely poor", "to make a basic living", "to dress warmly and eat one's fill", "to try to enrich (to disengage poverty)", "to be well-off" and "to be affluent". The data of average annual net income of all the 292 villages between 1990 and 2004 in rural Gongyi City, Henan Province were collected, veri-fied and classified. By using standard deviation, coefficient of variation and regression analysis, it is found that the Gongyi's rural economy has boosted up remarkably from the relative-poverty and absolute-poverty stages in 1990 to the well-off in 2004. However, the absolute differences between villages present a trend of enlargement, while the rela-tive differences fluctuating. On the other hand, spatial analysis of village-level economy shows that most villages with relatively high economic development level were located along national expressway and most villages with abso-lute-poverty lay in remote mountainous areas in 1990. Since the 1990s, the rapid urbanization and industrialization have had strongly positive effects on rural economic growth. Initial economic foundation, natural resources and tradi-tional techniques also contribute to village economy. From the perspective of geography, villages with location advan-tages, such as near urban center or industrial parks, have more chances for their economic development and the "core-periphery" economic structure has been presented in the process of rural development.展开更多
Least squares support vector machines (LS-SVMs), a nonlinear kemel based machine was introduced to investigate the prospects of application of this approach in modelling water vapor and carbon dioxide fluxes above a s...Least squares support vector machines (LS-SVMs), a nonlinear kemel based machine was introduced to investigate the prospects of application of this approach in modelling water vapor and carbon dioxide fluxes above a summer maize field using the dataset obtained in the North China Plain with eddy covariance technique. The performances of the LS-SVMs were compared to the corresponding models obtained with radial basis function (RBF) neural networks. The results indicated the trained LS-SVMs with a radial basis function kernel had satisfactory performance in modelling surface fluxes; its excellent approximation and generalization property shed new light on the study on complex processes in ecosystem.展开更多
基金Supported by National Natural Science Foundation of China(61001125)~~
文摘[Objective] The aim was to establish Elman neural network model to predict the dynamic changes of temperature. [Method] Considering the inherent nature of temperature, and dy dint of the temperature in Chongqing during 1951-2010, the Elman artificial neural network model was applied to predict the temperature. [Result] This simulation result suggested that the relative error was small and can have a good simulation to the future temperature changes. [Conclusion] The prediction result can guide agricultural production and further apply to the field of pricing the weather derivative products.
基金Under the auspices of Key Project of National Natural Science Foundation of China (No. 40535025)Project of Phi-losophy & Social Science of Henan Province (No. 2006CJJ022)
文摘Based on the research on the rural living standard in China in terms of annual net income per capita, we de-fine six types of village-level economy, i.e. "to be extremely poor", "to make a basic living", "to dress warmly and eat one's fill", "to try to enrich (to disengage poverty)", "to be well-off" and "to be affluent". The data of average annual net income of all the 292 villages between 1990 and 2004 in rural Gongyi City, Henan Province were collected, veri-fied and classified. By using standard deviation, coefficient of variation and regression analysis, it is found that the Gongyi's rural economy has boosted up remarkably from the relative-poverty and absolute-poverty stages in 1990 to the well-off in 2004. However, the absolute differences between villages present a trend of enlargement, while the rela-tive differences fluctuating. On the other hand, spatial analysis of village-level economy shows that most villages with relatively high economic development level were located along national expressway and most villages with abso-lute-poverty lay in remote mountainous areas in 1990. Since the 1990s, the rapid urbanization and industrialization have had strongly positive effects on rural economic growth. Initial economic foundation, natural resources and tradi-tional techniques also contribute to village economy. From the perspective of geography, villages with location advan-tages, such as near urban center or industrial parks, have more chances for their economic development and the "core-periphery" economic structure has been presented in the process of rural development.
基金Project supported by the National Science Fund for OutstandingYouth Overseas (No. 40328001) and the Key Research Plan of theKnowledge Innovation Project of the Institute of Geographic Sciencesand Natural Resources, Chinese Academy of Sciences (No.KZCXI-SW-01)
文摘Least squares support vector machines (LS-SVMs), a nonlinear kemel based machine was introduced to investigate the prospects of application of this approach in modelling water vapor and carbon dioxide fluxes above a summer maize field using the dataset obtained in the North China Plain with eddy covariance technique. The performances of the LS-SVMs were compared to the corresponding models obtained with radial basis function (RBF) neural networks. The results indicated the trained LS-SVMs with a radial basis function kernel had satisfactory performance in modelling surface fluxes; its excellent approximation and generalization property shed new light on the study on complex processes in ecosystem.
