Abstract: Along with the advancing new urbanization and living condition of the general public in China,ecological and environmental issues are becoming more significant. Giving the economic and environmental situation of China,a study area of four provinces(Shanxi,Shaanxi,Gansu and Ningxia)were selected by needs. As this research is oriented,the paper has constructed the evaluation index system of ecology and environment based on capacity pressure,status and response of ecosystem. All relevant data was adopted from the 2013 China statistical yearbook. Taking advantage of the PCA-GA-SVM evaluation,the paper thoroughly evaluated the ecological environment of the study area. The results suggested that the results from PCA-GA-SVM evaluation is more accurate than that from GA-SVM evaluation,and its convergence speed is faster than that of GA-SVM. The size of natural reserves in Gansu Province and Ningxia Province is larger than that in Shanxi Province and Shaanxi Province. Only Shaanxi Province has the forest coverage ranking at the 11^th of the nation,forest coverage in Shanxi, Gansu,Ningxia are all behind the 20^th place. On the analysis of sulfur dioxide emissions,dust emissions,industrial waste generation,wastewater emissions from the study area,Ningxia has the lowest level,followed by Gansu, Shaanxi,and Shanxi. Finally,the countermeasures and suggestions are put forward as follows:the ecological environment protection of the above places should have a "new status" under the "new normality"-to combine market mechanism,government subsidies and taxation strategies,stick to the ecological bottom line,develop green economy,green technology and clean production,reduce the industrial waste emissions,establish market for environmental protection,promote the governance on pollution control from the third party,improve the establishment of the ecological offsetting system,and integrate the concept of ecological civilization into the whole process of development and take a new route of urbanization in a manner of intensive,intelligent,green and low carbon.

Key words: principal components analysis, Genetic Algorithms, Support Vector Machine, ecology and environment evaluation