ArticleInternational journal of environmental research and public health2017
Priority of a Hesitant Fuzzy Linguistic Preference Relation with a Normal Distribution in Meteorological Disaster Risk Assessment.
Article in International journal of environmental research and public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Special Issue "Decision Models in Green Growth and Sustainable Development".International journal of environmental research and public health · 2018Article
- Nature Disaster Risk Evaluation with a Group Decision Making Method Based on Incomplete Hesitant Fuzzy Linguistic Preference Relations.International journal of environmental research and public health · 2018Article
- Evaluation of an Agricultural Meteorological Disaster Based on Multiple Criterion Decision Making and Evolutionary Algorithm.International journal of environmental research and public health · 2018Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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