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Classification Of Economic Competitiveness Of Cities In Shandong Province Based On Fuzzy Clustering

Posted on:2017-01-23Degree:MasterType:Thesis
Country:ChinaCandidate:S S LiFull Text:PDF
GTID:2308330485979095Subject:Operational Research and Cybernetics
Abstract/Summary:PDF Full Text Request
Fuzzy clustering analysis is an important research direction of cluster anal-ysis. In real life, we often encounter the situation that things are not clear or the boundary is not clear, And the fuzzy clustering analysis is proposed to solve this kind of problem. As a branch of multivariate statistical analysis method, it has been widely used in many fields, such as economy, society, transportation, medicine, meteorology, biology and so on. It has become an important tool of data analysis.Since the reform and opening up, the economy of Shandong Province has been developing rapidly, but the phenomenon of economic imbalance among cities in Shandong Province becomes more and more serious. In order to study the differences and similarities among the economic competitiveness of cities, And then clearly know the cause of the different economic competitiveness of cities, I classify the economic competitiveness of Shandong province. Because that some economic competitiveness indicators are fuzzy, a new fuzzy cluster-ing validity index is proposed based on the research of the fuzzy clustering validity index proposed by the predecessors in this paper, by improving the compactness factor, separation factor and overlap factor. Based on the new fuzzy clustering validity index, the optimal number of clusters is determined, and the fuzzy C mean algorithm is optimized by the method of principal com-ponent analysis.In this paper, I first establish the index system of economic competitive- ness, and then principal component analysis method is used to the original data. Through the dimension reduction and preliminary analysis, I get the ranking of the comprehensive economic competitiveness of the prefecture level cities. Finally, the principal component factor scores obtained after dimension-ality reduction are used as the original data to be input into the fuzzy C mean algorithm. And I calculate the value of the new fuzzy clustering validity index, so as to determine the best classification:the first category, Ji’nan, Qingdao, Zibo, Yantai, Weifang city; The second, Zaozhuang, Dongying, Jining, Tai’an, Weihai, Rizhao, Laiwu, Linyi, Dezhou, Liaocheng, Binzhou, Heze City.
Keywords/Search Tags:Fuzzy clustering analysis, New fuzzy clustering validity index, Principal component analysis, Economic competitiveness
PDF Full Text Request
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