Study on comprehensive evaluation model of attribute coordinate based on evaluation sample selection by K-means

Article type: Research Article

Authors: Xu, Guanglin^{a; 1} | Xu, Xiaolin^{b; 1; *}

Affiliations: [a] School of Information Management, Shanghai Lixin University of Accounting and Finance, Shanghai 201620, China | [b] College of International Vocational Education, Shanghai Second Polytechnic University, Shanghai 200120, China

Correspondence: [*] Corresponding author: Xiaolin Xu, School of Information Management, Shanghai Lixin University of Accounting and Finance, 2360 Jinhai Road, Pudong, Shanghai 200120, China. E-mail:[email protected]

Note: [1] The two authors contributed to this work.

Abstract: It is a very important step that the sample points are marked by experts in the comprehensive evaluation method based on attribute coordinate. At present, the sample points are selected randomly in some algorithms. However, this method possibly causes that the sample points has the homogeneity and can not represent the whole sample space, thus affecting the precision of evaluation results. In this paper, K-means clustering method is used to select sample points for evaluation, and the corresponding simulation experiment is also carried out. Then the simulation results showed the advantages of improved algorithm.

Keywords: Attribute theory method, comprehensive evaluation, K-means

DOI: 10.3233/JCM-170732

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 17, no. 3, pp. 463-472, 2017