Fuzzy Clustering Application Research In The Competitiveness Of Mineral Cities

Shanxi is rich in mineral resources, holds the very great proportion reserves in the national coal mine. Most of Shanxi cities are the mining cities. In recent years the country has paid much attention to the coal mine, many small coal mine industries in Shanxi have been reorganized. The measure is taken when the coal mine resource cities face resources exhaustion and economic development restriction. This paper proposed that suits the mining industry cities 22 comprehensive competitive power indicator systems. The mining industry cities usually sacrifice the resources environment as the price to take the high speed development, so this paper adds the green economy and the low-carbon economy indicator into the comprehensive competitive power indicator systems. The main purpose is to discover the merit and shortcoming in development of mining cities, developing the circulation economy according to local conditions.This paper according to the actual problem characteristic to use the fuzzy clustering algorithm of data mining algorithm which is the improvement of k-means algorithm to conduct the research, the fuzzy clustering algorithm is the method through establishment fuzzy similar relations to classify the objective things, this kind of partition has the relative nature, therefore is suitable for the complicated and diversified classified analysis. The traditional cluster analysis is one kind of hard partition; it divides strictly each identification object to some kind. But in fact the majority actual object not have strict attributes, they have ambiguity and intermediary in the behavior and the kind, so they suitable to carry on the soft partition. The fuzzy set theory has provided the powerful analysis tool for this kind of soft division. Therefore, fuzzy set theory by this article introduced to research the clustering of competitiveness of mining cities. This method has realized qualitative and the quantitative unifies, obtained the urban samples to belong to each category uncertainty degree, expressed urban samples intermediary class, established the urban samples regarding the category uncertainty description, and thus could more objectively reflect the reality the classified situation.According to the analysis, the data sets of the mining city needs preprocess. The pretreatment process is data selection, data cleaning, data conversion and data statute. By preprocessing the data set required the data table. This paper used the Java language to compile the fuzzy clustering algorithm programming, not only put this procedure to the Weka software in realizes the advantage of this algorithm but also to use the advantage of Weka software. This paper used the improved Weka to mining the cities of Shanxi province. The application of fuzzy clustering algorithm in cities competition evaluation may avoid the subjective factor; it can cluster competitive competences of the cities objectively.Through practical application, verify the fuzzy clustering analysis of the competitiveness of mining cities in the model is reasonable and effective. Model evaluation results can not only classify the cities, but also demonstrate the link between urban indicators. Based on the results, mining cities can make development strategy according to the local conditions.