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Multi-Attribute Decision Making with Interval-Valued Hesitant Fuzzy Information, a Novel Synthetic Grey Relational Degree Method
Volume 29, Issue 3 (2018), pp. 517–537
Pub. online: 1 January 2018      Type: Research Article      Open accessOpen Access
Received
1 October 2017
Accepted
1 May 2018
Published
1 January 2018

Abstract

Quantitative and qualitative fuzzy information measures have been proposed to solve multi-attribute decision making (MADM) problems with interval–valued hesitant fuzzy information from different points. We analyse the existing fuzzy information measures of the interval-valued hesitant fuzzy sets (IVHFSs) in detail and classify them into two categories. One is based on the closeness of the data, such as the distance, and the other is based on the linear relationship or variation tendency, such as the correlation coefficient. These two kinds of information measures are actually partial measures which pay attention to only one factor of the data. Therefore, we construct a novel synthetic grey relational degree by considering both the closeness and the variation tendency factors of the data to improve the existing information measures and enhance the grey relational analysis (GRA) theory for IVHFSs. However, the notion of the synthetic grey relational degree is not only restricted to the IVHFSs but can be extended to other sets. Furthermore, we employ two practical MADM examples about emergency management evaluation and pattern recognition to validate and compare the proposed synthetic grey relational degree with other information measures, which demonstrate its superiorities in discrimination and accuracy.

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Biographies

Sun Guidong
dwhsgd@163.com

G. Sun is currently pursuing the PhD degree at Naval Aviation University. He has authored and co-authored over 15 research papers and published some papers in leading international journals, such as Expert Systems with Applications, Applied Soft Computing, and the International Journal of Fuzzy Systems. His research interests include fuzzy multi criteria decision-making, information fusion, and pattern recognition. He also serves as a reviewer of the several distinguished journals as KBS and IEEE TKDE.

Guan Xin
gxtongwin@163.com

X. Guan is currently a full-time professor and a doctor tutor at Naval Aviation University. She is an author of four books, over 100 articles, and over 10 inventions. Her research interests include evidence reasoning, signal processing, and target recognition. She received the award in the Program for New Century Excellent Talents by the Minister of Education in 2011 and was awarded the Taishan Scholar in 2017. She is an active journal reviewer of journals such as Chinese Journal of Aeronautics, The Chinese Journal of Electronics, Science China, and so on.

Yi Xiao

X. Yi is currently a full-time professor and a doctor tutor in Naval Aviation University. He has published over 50 papers and three academic monographs. His major is wireless sensor network and intelligent information processing.

Zhou Zheng

Z. Zhou is currently an associate professor in Naval Aviation University. His research interests include cyberspace countermeasures and computer networks.


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Keywords
multi-attribute decision making (MADM) interval-valued hesitant fuzzy sets (IVHFSs) synthetic grey relational degree information measures

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