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Journal of Information Science
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Research on a principal components decision algorithm based on information entropy

Shifei Ding

School of Computer Science and Technology, China University of Mining and Technology; Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, dingsf{at}cumt.edu.cn

Yongping Zhang

School of Computer Science and Technology, China University of Mining and Technology

Xiaofeng Lei

School of Computer Science and Technology, China University of Mining and Technology

Xinzheng Xu

School of Computer Science and Technology, China University of Mining and Technology

Xin Wang

School of Computer Science and Technology, China University of Mining and Technology

Li Wang

School of Computer Science and Technology, China University of Mining and Technology

Qing He

Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences

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.

Key Words: algorithm • information entropy • land quality • objective entropy weight • principal component decision

This version was published on February 1, 2009

Journal of Information Science, Vol. 35, No. 1, 120-127 (2009)
DOI: 10.1177/0165551508094049
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