doi: 10.4304/jsw.8.10.2489-2494
An Optimized Grey Cluster Model for Evaluating Quality of Labor Force
2School of Economics & International Trade, Zhejiang University of Finance & Economics, Hangzhou, China
Abstract—In this study, the concept of relative membership degree is proposed to investigate grey optimal cluster evaluation. Besides, the correlation coefficient between sample observation value and standard eigenvalue is used to reflect the similarity degree of evaluation objective and each cluster centre. Based on those mentioned above and concept of relative membership degree, an optimized grey cluster evaluation model is established. Meanwhile, Lagrange function is constructed to obtain the relative membership degree. According to the size of relative membership degree, evaluation objectives are classified. Thereby, the fuzzy membership degree information in classification is effectively integrated into grey cluster evaluation. Finally, the effectiveness and practicability of this model is verified through the labor force quality evaluation of three provinces in East China.
Index Terms—Grey cluster, triangle whiten weight function, grey correlation analysis, relative membership degree, dynamic quality evaluation.
Cite: Ling-ling Pei, Zheng-xin Wang, "An Optimized Grey Cluster Model for Evaluating Quality of Labor Force," Journal of Software vol. 8, no. 10, pp. 2489-2494, 2013.
General Information
ISSN: 1796-217X (Online)
Abbreviated Title: J. Softw.
Frequency: Quarterly
APC: 500USD
DOI: 10.17706/JSW
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Cecilia Xie
Abstracting/ Indexing: DBLP, EBSCO,
CNKI, Google Scholar, ProQuest,
INSPEC(IET), ULRICH's Periodicals
Directory, WorldCat, etcE-mail: jsweditorialoffice@gmail.com
-
Oct 22, 2024 News!
Vol 19, No 3 has been published with online version [Click]
-
Jan 04, 2024 News!
JSW will adopt Article-by-Article Work Flow
-
Apr 01, 2024 News!
Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec) [Click]
-
Apr 01, 2024 News!
Papers published in JSW Vol 18, No 1- Vol 18, No 6 have been indexed by DBLP [Click]
-
Jun 12, 2024 News!
Vol 19, No 2 has been published with online version [Click]