Having researched for many years, seismologists in China presented about 80 earthquake prediction factors which reflected omen information of earthquake. How to concentrate the information that the 80 earthquake predi...Having researched for many years, seismologists in China presented about 80 earthquake prediction factors which reflected omen information of earthquake. How to concentrate the information that the 80 earthquake prediction factors have and how to choose the main factors to predict earthquakes precisely have become one of the topics in seismology. The model of principal component-discrimination consists of principal component analysis, correlation analysis, weighted method of principal factor coefficients and Mahalanobis distance discrimination analysis. This model combines the method of maximization earthquake prediction factor information with the weighted method of principal factor coefficients and correlation analysis to choose earthquake prediction variables, applying Mahalanobis distance discrimination to establishing earthquake prediction discrimination model. This model was applied to analyzing the earthquake data of Northern China area and obtained good prediction results.展开更多
With integration of renewable energy and use of non-linear loads in power systems,the power quality problem is increasingly attracting attention of researchers.In China,standards for individual power quality indexes a...With integration of renewable energy and use of non-linear loads in power systems,the power quality problem is increasingly attracting attention of researchers.In China,standards for individual power quality indexes are set.However,when evaluating power quality in practice,individual indexes cannot directly reflect a comprehensive level of power quality.In this paper,a comprehensive analysis of various indexes is conducted to obtain a unified parameter for describing the characteristics of power quality from an overall perspective.First,weight values of power quality indexes are calculated by combining the subjective and objective weight.Then,based on the principal components of the projection method,projection values of boundary data and data to be evaluated are obtained.Finally,using these projection values,a grade range for power quality data is located.A practical case study is presented to show the validity of the proposed method for evaluating power quality.展开更多
Connotation of land competitiveness is expatiated from both the narrow sense and broad sense. Evaluation index system of land competitiveness is established according to the 2008 China Statistical Yearbook and 2008 Ch...Connotation of land competitiveness is expatiated from both the narrow sense and broad sense. Evaluation index system of land competitiveness is established according to the 2008 China Statistical Yearbook and 2008 China Land Resources Statistical Yearbook. Efficiency Coefficient Method and Principal Component Analysis Method are used to evaluate the land competitiveness of 31 provincial units in China. Result shows that in the year 2007, land competitiveness gradually decreases from southeast to northwest. The land competitiveness and GDP per unit land have significant negative correlation. The rank of approved new construction land has low positive correlation with the rank of land competitiveness in China. This indicates that there is little correlation between the allocation of regional new construction land and the land use efficiency. Therefore, it is suggested that regional allocation of new construction land should be treated differently based on the evaluation result of land competitiveness.展开更多
文摘Having researched for many years, seismologists in China presented about 80 earthquake prediction factors which reflected omen information of earthquake. How to concentrate the information that the 80 earthquake prediction factors have and how to choose the main factors to predict earthquakes precisely have become one of the topics in seismology. The model of principal component-discrimination consists of principal component analysis, correlation analysis, weighted method of principal factor coefficients and Mahalanobis distance discrimination analysis. This model combines the method of maximization earthquake prediction factor information with the weighted method of principal factor coefficients and correlation analysis to choose earthquake prediction variables, applying Mahalanobis distance discrimination to establishing earthquake prediction discrimination model. This model was applied to analyzing the earthquake data of Northern China area and obtained good prediction results.
基金supported by National Natural Science Foundation of China(NSFC)(51477111)National Key Research and Development Program of China(2016YFB0901104).
文摘With integration of renewable energy and use of non-linear loads in power systems,the power quality problem is increasingly attracting attention of researchers.In China,standards for individual power quality indexes are set.However,when evaluating power quality in practice,individual indexes cannot directly reflect a comprehensive level of power quality.In this paper,a comprehensive analysis of various indexes is conducted to obtain a unified parameter for describing the characteristics of power quality from an overall perspective.First,weight values of power quality indexes are calculated by combining the subjective and objective weight.Then,based on the principal components of the projection method,projection values of boundary data and data to be evaluated are obtained.Finally,using these projection values,a grade range for power quality data is located.A practical case study is presented to show the validity of the proposed method for evaluating power quality.
基金Supported by the Natural Science Foundation of China (70803032)
文摘Connotation of land competitiveness is expatiated from both the narrow sense and broad sense. Evaluation index system of land competitiveness is established according to the 2008 China Statistical Yearbook and 2008 China Land Resources Statistical Yearbook. Efficiency Coefficient Method and Principal Component Analysis Method are used to evaluate the land competitiveness of 31 provincial units in China. Result shows that in the year 2007, land competitiveness gradually decreases from southeast to northwest. The land competitiveness and GDP per unit land have significant negative correlation. The rank of approved new construction land has low positive correlation with the rank of land competitiveness in China. This indicates that there is little correlation between the allocation of regional new construction land and the land use efficiency. Therefore, it is suggested that regional allocation of new construction land should be treated differently based on the evaluation result of land competitiveness.
