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An Emergency Decision-Making Method for Coal Spontaneous Combustion Based on Improved Prospect Theory.

Authors :
Zeng, Jingwei
Jing, Guoxun
Zhu, Qifeng
Source :
Processes; Jan2024, Vol. 12 Issue 1, p151, 17p
Publication Year :
2024

Abstract

In response to the limited available information during the initial stages of coal spontaneous combustion and the influence of decision makers' risk preferences on decision-making, this paper proposes an emergency decision-making method for coal spontaneous combustion that integrates grey correlation degree and TOPSIS with an enhanced prospect theory. Firstly, a normalized weighted evaluation matrix is established for the emergency response plan of coal spontaneous combustion, and the entropy method is utilized to determine the weights of various indexes. Then, considering the imperfect rationality of decision makers and their diverse individual risk preferences, they are categorized into three types: risk-seeking type, risk-neutral type, and risk-averse type. The corresponding risk coefficients are determined based on these different types. Positive and negative ideal solutions are taken as reference points, and matrices representing gains and losses are constructed. The grey correlation degree is introduced to calculate both positive and negative prospect values based on these matrices. Moreover, the prospect value for each emergency response plan is calculated, respectively, based on different types of decision makers, and the entropy method is used to assign weights to decision makers according to their respective risk preferences. Consequently, based on these prospect values and the weights, comprehensive prospect values for each emergency response plan are obtained and ranked to identify the optimal one. Finally, in order to validate the effectiveness of our proposed approach, a case study is conducted, and the results obtained from this case study are discussed and compared with those from other methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22279717
Volume :
12
Issue :
1
Database :
Complementary Index
Journal :
Processes
Publication Type :
Academic Journal
Accession number :
175131605
Full Text :
https://doi.org/10.3390/pr12010151