A relatively perfect coalmine fire risk-evaluating and order-arranging model that includes sixteen influential factors was established according to the statistical information of the fully mechanized coalface ground o...A relatively perfect coalmine fire risk-evaluating and order-arranging model that includes sixteen influential factors was established according to the statistical information of the fully mechanized coalface ground on the uncertainty measure theory. Then the single-index measure function of sixteen influential factors and the calculation method of computing the index weight ground on entropy theory were respectively established. The value assignment of sixteen influential factors was carried out by the qualitative analysis and observational data, respectively, in succession. The sequence of fire danger class of four experimental coalfaces could be obtained by the computational aids of Matlab according to the confidence level criterion. Some conclusions that the fire danger class of the No.l, No.2 and No.3 coalface belongs to high criticality can be obtained. But the fire danger class of the No.4 coalface belongs to higher criticality. The fire danger class of the No.4 coalface is more than that of the No.2 coalface. The fire danger class of the No.2 coalface is more than that of the No.1 coalface. Finally, the fire danger class of the No.1 coalface is more than that of the No.3 coalface.展开更多
The fragility of ecosystem health has become a key factor hindering the sustainable development of the ecological environment. Through a review of published research from domestic and foreign scholars, starting from t...The fragility of ecosystem health has become a key factor hindering the sustainable development of the ecological environment. Through a review of published research from domestic and foreign scholars, starting from the endogenous logic of studies in the field of ecosystem vulnerability(EV), this paper sorts out the literature on the aspects of measurement models, prediction methods and risk assessment, comprehensively defines the research category and scientific framework of EV, and analyzes the research ideas and development trends. We arrived at the following conclusions: 1) The connotation of ecosystem vulnerability not only embodies the change in the vulnerability of the natural environment, but it also reflects the irreversible damage to the ecosystem caused by excessive development and industrial production activities. 2) The setting of ecosystem vulnerability indices should aim to fully reflect the essential features of that vulnerability, which should include the index systems of natural, social, economic and other related factors. 3) There are many types of ecosystem vulnerability measurement methods, prediction models and risk evaluation models, which have different focuses and advantages. The most appropriate method should be adopted for conducting comprehensive and systematic evaluation, prediction and estimation according to the different representation and evolution mechanisms of the chosen research object and regional ecosystem vulnerability. 4) Based on the regional system characteristics, corresponding risk management measures should be proposed, and pertinent policy suggestions should be put forward to improve the ecological safety and sustainable development of an ecologically vulnerable area.展开更多
In order to improve the precision of personal credit risk assessment, applying rough set and neural network to the credit risk scoring prediction problem in an attempt to suggest a new model with better classification...In order to improve the precision of personal credit risk assessment, applying rough set and neural network to the credit risk scoring prediction problem in an attempt to suggest a new model with better classification accuracy. To evaluate the prediction accuracy of the model, we compare its performance with those of SVM, linear discriminate analysis, logistic regression analysis, K-nearest neighbors, classification and regression tree, neural network and PCA-NN. The experimental results show the model have a very good prediction accuracy展开更多
基金Supported by the National Foundation of China(50974055)the Program for Changjiang Scholars and Innovative Research Team in University(IRT0618)Henan Province Basic and Leading-edge Technology Research Program(082300463205)
文摘A relatively perfect coalmine fire risk-evaluating and order-arranging model that includes sixteen influential factors was established according to the statistical information of the fully mechanized coalface ground on the uncertainty measure theory. Then the single-index measure function of sixteen influential factors and the calculation method of computing the index weight ground on entropy theory were respectively established. The value assignment of sixteen influential factors was carried out by the qualitative analysis and observational data, respectively, in succession. The sequence of fire danger class of four experimental coalfaces could be obtained by the computational aids of Matlab according to the confidence level criterion. Some conclusions that the fire danger class of the No.l, No.2 and No.3 coalface belongs to high criticality can be obtained. But the fire danger class of the No.4 coalface belongs to higher criticality. The fire danger class of the No.4 coalface is more than that of the No.2 coalface. The fire danger class of the No.2 coalface is more than that of the No.1 coalface. Finally, the fire danger class of the No.1 coalface is more than that of the No.3 coalface.
基金The National Social Science Fundation of China (17XJY020)The National Natural Science Foundation of China (71963028)The Discipline Construction Project for Ningxia Institutions of Higher Education (Discipline of Theoretical Economics)(NXYLXK2017B04)。
文摘The fragility of ecosystem health has become a key factor hindering the sustainable development of the ecological environment. Through a review of published research from domestic and foreign scholars, starting from the endogenous logic of studies in the field of ecosystem vulnerability(EV), this paper sorts out the literature on the aspects of measurement models, prediction methods and risk assessment, comprehensively defines the research category and scientific framework of EV, and analyzes the research ideas and development trends. We arrived at the following conclusions: 1) The connotation of ecosystem vulnerability not only embodies the change in the vulnerability of the natural environment, but it also reflects the irreversible damage to the ecosystem caused by excessive development and industrial production activities. 2) The setting of ecosystem vulnerability indices should aim to fully reflect the essential features of that vulnerability, which should include the index systems of natural, social, economic and other related factors. 3) There are many types of ecosystem vulnerability measurement methods, prediction models and risk evaluation models, which have different focuses and advantages. The most appropriate method should be adopted for conducting comprehensive and systematic evaluation, prediction and estimation according to the different representation and evolution mechanisms of the chosen research object and regional ecosystem vulnerability. 4) Based on the regional system characteristics, corresponding risk management measures should be proposed, and pertinent policy suggestions should be put forward to improve the ecological safety and sustainable development of an ecologically vulnerable area.
文摘In order to improve the precision of personal credit risk assessment, applying rough set and neural network to the credit risk scoring prediction problem in an attempt to suggest a new model with better classification accuracy. To evaluate the prediction accuracy of the model, we compare its performance with those of SVM, linear discriminate analysis, logistic regression analysis, K-nearest neighbors, classification and regression tree, neural network and PCA-NN. The experimental results show the model have a very good prediction accuracy
