关键词: 信誉度, 供应链, 聚类中心, 质量检验, K-Means聚类

Abstract: Aimed at the contradiction that the coal quality information is scattered and the quality-valuation policy requires the precision of its quality, which is existing in coal sales currently, a new K-Means clustering algorithm optimizing the selection of the initial clustering center is proposed, and a detailed analysis and data mining on the data of the coal quality inspection produced by a large-scale coal enterprise and its alliance customers is conducted, in order to gain the statistical rules of the traders’ quality inspection behaviors, and grade credibility hierarchies of the traders on both sides, thus transforming the uncertain quality indicators into the deterministic evaluation of the traders’ quality inspection behaviors. On one hand, it can provide reference for the coal enterprises to divide the responsibility of quality inspection reasonably when the quality disputes of the traders occur, and supervise and guide the quality inspection managements of mines and customers at the same time; on the other hand, it can provide ancillary support for the sales decision of the coal enterprises.

Key words: credibility, supply chain, clustering center, quality inspection, K-Means clustering