A novel multiple attribute decision-making approach for evaluation of emergency management schemes under picture fuzzy environment-Reference-Cited by-同舟云学术

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A novel multiple attribute decision-making approach for evaluation of emergency management schemes under picture fuzzy environment

Published:2021-03-19 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Rong Yuan,Liu Yi,Pei Zheng

Funder

National Natural Science Foundation of China

Scientific and Technological Project of Sichuan Province

Sichuan Province Youth Science and Technology Innovation Team

Zhejiang Province Public Welfare Technology Application Research Project

Scientific Research Project of Department of Education of Sichuan Province

Scientific Research Project of Neijiang Normal University

Innovation Fund of Postgraduate Xihua University

University Students Innovation and Entrepreneurship Project of Xihua Cup

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

http://link.springer.com/content/pdf/10.1007/s13042-021-01280-1.pdf

Reference58 articles.

1. Ju Y, Wang A, You T (2015) Emergency alternative evaluation and selection based on ANP, DEMATEL, and TL-TOPSIS. Nat Hazards 75(2):347–379

2. Wang L, Wang YM, Martínez L (2017) A group decision method based on prospect theory for emergency situations. Inf Sci 418:119–135

3. Qi K, Wang Q, Duan Q, Gong L, Sun J, Liew KM, Jiang L (2018) A multi criteria comprehensive evaluation approach for emergency response capacity with interval 2-tuple linguistic information. Appl Soft Comput 72:419–441

4. Li M, Cao P (2019) Extended TODIM method for multi-attribute risk decision making problems in emergency response. Comput Ind Eng 135:1286–1293

5. Liu Y, Wang Y, Xu M, Xu G (2019) Emergency alternative evaluation using extended trapezoidal intuitionistic fuzzy thermodynamic approach with prospect theory. Int J Fuzzy Syst 21(6):1801–1817

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