| This paper according to the theory of urban land intensive utilization, the support vector machine(SVM) theory and ant colony algorithm theory as the theoretical guidance,and combining the current our country new urbanization construction background, using qualitative and quantitative analysis, normative analysis and empirical research with the combination of research methods, to our country in the new urbanization construction land intensive use of empirical research, and on this basis, according to China’s regional urban land intensive utilization present situation, proposed the enhance the level of land intensive utilization, some countermeasures and Suggestions to improve the quality of new urbanization construction.The first chapter as the full text research review, a detailed carding about land intensive utilization at home and abroad, and new research status quo of land intensive utilization evaluation in the construction of urbanization, and through the study of existing land intensive utilization theory, this paper, the research point of view in this paper and in the form of chart is introduced in this paper, in China the new evaluation method for the intensive utilization of land in the urbanization construction.The second chapter discusses the urban land intensive utilization evaluation in the construction of the new urbanization involved in the basic theory, respectively discusses the new urbanization, land intensive utilization, and the characteristics of the intensive utilization of land in the construction of new type of urbanization and urban land intensive utilization of different development direction; From the narrow sense, broad and comprehensive definition level clear new town construction in the basic connotation of intensive utilization of urban land. Through to the urban land intensive utilization in the construction of the new urbanization analysis of influence factors for later set up evaluation index system of urban land intensive utilization. At last, through summary analysis of the traditional analysis of traditional evaluation method, lead to this essay evaluation method using ant colony optimization support vector machine(SVM).The third chapter mainly introduces the support vector machine(SVM) theory and the basic principle of ant colony algorithm theory, and the new learning method based on support vector machine(SVM) the shortage of the research, discusses the features of global searching through the ant colony algorithm to optimize the parameters of the support vector machine selection problem, and create the ant colony algorithm optimization support vector machine(SVM) model.The fourth chapter is the emphasis of the establishment of land intensive, focused on the construction of the new urbanization in the use of the evaluation index system is studied, according to the basic principles of the establishment of evaluation index system,the research dynamic of domestic and foreign scholars on the intensive use of land, and combined with the guiding ideology of the new urbanization construction, detailed collection of nearly 2000 of China’s provinces an effective index data, and the primary index data for quantitative analysis to filter redundant indexes, established a new accord with China’s new urbanization construction thought of the city land intensive use index system. The use of ACO-SVM programming to establish the city land intensive use evaluation index system to evaluate the level of land intensive, thirty-one provincial-level administrative region in our country by using the relative order of precedence, and according to the comparative analysis between the actual value of the predicted value,summed up the evaluation method of the city land intensive use of ant colony optimization support vector machine based on the ideal the evaluation results. Finally discuss on land intensive utilization in China is divided into regions, and puts forward corresponding suggestions and countermeasures.The fifth chapter is on the basis of above analysis, summarize the research achievements and shortcomings of this paper. |