文献类型：期刊文献

英文题名：Multicriteria decision-making method using the correlation coefficient under single-valued neutrosophic environment

作者：Ye, Jun[1,2]

机构：[1]Shaoxing Univ, Dept Elect & Informat Engn, Shaoxing 312000, Zhejiang, Peoples R China;[2]Southern Polytech State Univ, Sch Engn, Marietta, GA 30060 USA

年份：2013

卷号：42

期号：4

起止页码：386

外文期刊名：INTERNATIONAL JOURNAL OF GENERAL SYSTEMS

收录：SCI-EXPANDED(收录号：WOS:000315676500005)、、EI(收录号：20130916050022)、Scopus(收录号：2-s2.0-84874118713)、WOS

基金：Jun Ye is a Professor in the Department of Electrical and Information Engineering, Shaoxing University, China. Now he is a visiting scholar of the School of Engineering of Southern Polytechnic State University in USA. He has more than 30 years of experience in teaching and research. His current area of research includes Multi-criteria Decision-Making, Soft Computing, Robotics and Automation, Intelligent Control, Pattern Recognitions, Fault Diagnosis, and Mechanical Design. He has published more than 90 papers in journals. He has written few books related to his research work. He has finished a few projects sponsored by government of China.

语种：英文

外文关键词：neutrosophic set; single-valued neutrosophic set; correlation; correlation coefficient; multicriteria decision-making

外文摘要：The paper presents the correlation and correlation coefficient of single-valued neutrosophic sets (SVNSs) based on the extension of the correlation of intuitionistic fuzzy sets and demonstrates that the cosine similarity measure is a special case of the correlation coefficient in SVNS. Then a decision-making method is proposed by the use of the weighted correlation coefficient or the weighted cosine similarity measure of SVNSs, in which the evaluation information for alternatives with respect to criteria is carried out by truth-membership degree, indeterminacy-membership degree, and falsity-membership degree under single-valued neutrosophic environment. We utilize the weighted correlation coefficient or the weighted cosine similarity measure between each alternative and the ideal alternative to rank the alternatives and to determine the best one(s). Finally, an illustrative example demonstrates the application of the proposed decision-making method.