A Research on Competitiveness of Guangxi City——Based on System Clustering Method and Principal Component Analysis Method

A total of 10 indices of regional economic development in Guangxi are selected.According to the relevant economic data,regional economic development in Guangxi is analyzed by using System Clustering Method and Principal Component Analysis Method.Result shows that System Clustering Method and Principal Component Analysis Method have revealed similar results analysis of economic development level.Overall economic strength of Guangxi is weak and Nanning has relatively high scores of factors due to its advantage of the political,economic and cultural center.Comprehensive scores of other regions are all lower than 1,which has big gap with the development of Nanning.Overall development strategy points out that Guangxi should accelerate the construction of the Ring Northern Bay Economic Zone,create a strong logistics system having strategic significance to national development,use the unique location advantage and rely on the modern transportation system to establish a logistics center and business center connecting the hinterland and the Asean Market.Based on the problems of unbalanced regional economic development in Guangxi,we should speed up the development of service industry in Nanning,construct the circular economy system of industrial city,and accelerate the industrialization process of tourism city in order to realize balanced development of regional economy in Guangxi,China.

Mathematical Tools of Cluster Analysis

The paper deals with cluster analysis and comparison of clustering methods. Cluster analysis belongs to multivariate statistical methods. Cluster analysis is defined as general logical technique, procedure, which allows clustering variable objects into groups-clusters on the basis of similarity or dissimilarity. Cluster analysis involves computational procedures, of which purpose is to reduce a set of data on several relatively homogenous groups-clusters, while the condition of reduction is maximal and simultaneously minimal similarity of clusters. Similarity of objects is studied by the degree of similarity (correlation coefficient and association coefficient) or the degree of dissimilarity-degree of distance (distance coefficient). Methods of cluster analysis are on the basis of clustering classified as hierarchical or non-hierarchical methods.

Assessment of Comprehensive Carrying Capacity of Land Resources Based on Land Functions

Based on relevant research results,from the perspective of land use functions,an evaluation indicator system of carrying capacity of land resources composed of three second-grade indicators( production,living and ecological carrying capacity) including 24 third-grade indicators was established,and the carrying capacity of land resources in ten cities of Shaanxi Province in 2013 was assessed and analyzed by using mean square error analysis method and hierarchical clustering method. The results showed that the three types of carrying capacity in most cities of Shaanxi Province are shown as follows: ecological carrying capacity > living carrying capacity > production carrying capacity,and the differences between various regions in a single type of carrying capacity basically accorded with the actual situation of development in each city; there were obvious differences between various cities in the comprehensive carrying capacity of land resources,which was basically consistent with regional economic and social development.