Evidence map›Paper›PMID 29652868›Full record

ArticleInternational journal of environmental research and public health2018

Nature Disaster Risk Evaluation with a Group Decision Making Method Based on Incomplete Hesitant Fuzzy Linguistic Preference Relations.

Ming Tang, Huchang Liao, Zongmin Li, Zeshui Xu

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ming TangBusiness School, Sichuan University, Chengdu 610064, China. tangming0716@163.com.
Huchang LiaoBusiness School, Sichuan University, Chengdu 610064, China. liaohuchang@scu.edu.cn.
Zongmin LiBusiness School, Sichuan University, Chengdu 610064, China. lizongmin@scu.edu.cn.
Zeshui XuBusiness School, Sichuan University, Chengdu 610064, China. xuzeshui@263.net.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Because the natural disaster system is a very comprehensive and large system, the disaster reduction scheme must rely on risk analysis. Experts' knowledge and experiences play a critical role in disaster risk assessment. The hesitant fuzzy linguistic preference relation is an effective tool to express experts' preference information when comparing pairwise alternatives. Owing to the lack of knowledge or a heavy workload, information may be missed in the hesitant fuzzy linguistic preference relation. Thus, an incomplete hesitant fuzzy linguistic preference relation is constructed. In this paper, we firstly discuss some properties of the additive consistent hesitant fuzzy linguistic preference relation. Next, the incomplete hesitant fuzzy linguistic preference relation, the normalized hesitant fuzzy linguistic preference relation, and the acceptable hesitant fuzzy linguistic preference relation are defined. Afterwards, three procedures to estimate the missing information are proposed. The first one deals with the situation in which there are only n-1 known judgments involving all the alternatives; the second one is used to estimate the missing information of the hesitant fuzzy linguistic preference relation with more known judgments; while the third procedure is used to deal with ignorance situations in which there is at least one alternative with totally missing information. Furthermore, an algorithm for group decision making with incomplete hesitant fuzzy linguistic preference relations is given. Finally, we illustrate our model with a case study about flood disaster risk evaluation. A comparative analysis is presented to testify the advantage of our method.

Indexed as

AlgorithmsDecision MakingFuzzy LogicNatural DisastersLinguisticsRisk Assessmentadditive consistencygroup decision makingincomplete hesitant fuzzy linguistic preference relationnature disaster risk evaluation

Identifiers

PMID29652868
PMCPMC5923793

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