Priority of a Hesitant Fuzzy Linguistic Preference Relation with a Normal Distribution in Meteorological Disaster Risk Assessment

Lihong Wang and Zaiwu Gong
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Lihong Wang: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, College of Economics and Management, Nanjing University of Information Science and Technology, Nanjing 210044, China
Zaiwu Gong: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, College of Economics and Management, Nanjing University of Information Science and Technology, Nanjing 210044, China

IJERPH, 2017, vol. 14, issue 10, 1-16

Abstract: As meteorological disaster systems are large complex systems, disaster reduction programs must be based on risk analysis. Consequently, judgment by an expert based on his or her experience (also known as qualitative evaluation) is an important link in meteorological disaster risk assessment. In some complex and non-procedural meteorological disaster risk assessments, a hesitant fuzzy linguistic preference relation (HFLPR) is often used to deal with a situation in which experts may be hesitant while providing preference information of a pairwise comparison of alternatives, that is, the degree of preference of one alternative over another. This study explores hesitation from the perspective of statistical distributions, and obtains an optimal ranking of an HFLPR based on chance-restricted programming, which provides a new approach for hesitant fuzzy optimisation of decision-making in meteorological disaster risk assessments.

Keywords: meteorological disaster risk assessment; hesitant fuzzy linguistic preference relation (HFLPR); additive consistency; normal distribution; chance-restricted programming; priority (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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