The Research And Application Of Grey Data Mining On Type Selection Of Product

With the rapid development of manufacturing industry, a large number of various models of machines have been produced. At the same time, people have a higher demand of synthetic performance of machinery. Thus, it is necessary to develop a decision making software system to help the consumers choose suitable goods among the numerous similar products.Technology of data mining can obtain undiscovered but potential useful information and knowledge among a large amount of applicable data, which are often incomplete, fuzzy and random. While the research object of grey system theory is deficient information, which means part of the information is known, but the other part of the information is still unknown. Grey system theory extracts useful information from the known information to realize the recognization of the systematic information. The purpose of this paper is: to compare the advantages and disadvantages of data mining technology with grey system theory; to build a data mining algorithmic model of comprehensive performance judgment of product on basis of grey system theory; combine with the cases to validate the applicability of the data mining algorithmic model; at last develop a computer application software which is applicable to judge the comprehensive performances of a product based on this data mining algorithmic model.The main characteristic and innovation of this paper lie in three following aspects. Firstly, we apply some of grey system theory arithmetics into technology of data mining to overcome some problems from the single application. View grey system theory as useful supplement of the technology of data mining, and build grey data mining algorithmic model, which is applicable to judgment of product synthetic performances, and combine with some cases to analyze and validate. In such a way, we developed a suitable computer applications software. Secondly, we changed the traditional analytical method of grey theory of subjective weights and objective weights to resolve the problem of calculation subjectively, and to realize the integration of subjective weights and objective weights, and obtained the results of truth and credibility; Lastly, we validated all case with both TOPSIS- arithmetic and grey data mining arithmetic. We got almost the same results.