Research on a principal components decision algorithm based on information entropy

  • Authors:

  • Shifei Ding; Yongping Zhang; Xiaofeng Lei; Xinzheng Xu; Xin Wang; Li Wang; Qing He

  • Affiliations:

  • School of Computer Science and Technology, China Universityof Mining and Technology/ Key Laboratory of Intelligent Information Processing,Institute of Computing Technology, Chinese Academy of Scie ...;School of Computer Science and Technology, China Universityof Mining and Technology;School of Computer Science and Technology, China Universityof Mining and Technology;School of Computer Science and Technology, China Universityof Mining and Technology;School of Computer Science and Technology, China Universityof Mining and Technology;School of Computer Science and Technology, China Universityof Mining and Technology;Key Laboratory of Intelligent Information Processing,Institute of Computing Technology, Chinese Academy of Sciences

  • Venue:
  • Journal of Information Science
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

A principal component decision algorithm based on information entropy is provided in this paper. First we summarize the information entropy theory, provide the concept of objective entropy weight (OEW) and provide a construction method of OEW; we determine a principal component decision rule by weighted normalization processing of a known dataset and in the process establish the principal component decision algorithm on the basis of information entropy and apply it in a comprehensive decision on land quality. The results show that the method provided in our paper is effective and reasonable.