Fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights

Chen, Shyi‐Ming; Munif, Abdul; Chen, Guey-Shya; Liu, Hsiang-Chuan; Kuo, Bor‐Chen

doi:10.1016/j.eswa.2011.12.004

Cited by 119 publications

(66 citation statements)

References 14 publications

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“…The values a; b; c and d are real, h L is called the left height of the GFNÃ, h R is called the right height of the GFN, h L 2 ½0; 1 and h R 2 ½0; 1 [5]. For now, let FðRÞ be the set of all GFNs with different left height and right height.…”

Section: Generalised Fuzzy Numbermentioning

confidence: 99%

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Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

2015

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Section: Generalised Fuzzy Numbermentioning

confidence: 99%

“…The arithmetic of p-norm GFNs with different left height and right height are reviewed from Chen [5].…”

Section: Arithmetic Operationsmentioning

confidence: 99%

Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

2015

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“…Since Zadeh [35] proposed fuzzy sets, it has been widely applied in various fields [36][37][38][39][40] and many extensions based on fuzzy set have been developed [41,42]. HFSs, as extensions of fuzzy sets, were firstly presented by Torra [32].…”

Section: Hesitant Fuzzy Setsmentioning

confidence: 99%

Selecting the Optimal Mine Ventilation System via a Decision Making Framework under Hesitant Linguistic Environment

2018

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Ventilation systems are amongst the most essential components of a mine. As the indicators of ventilation systems are in general of ambiguity or uncertainty, the selection of ventilation systems can therefore be regarded as a complex fuzzy decision making problem. In order to solve such problems, a decision making framework based on a new concept, the hesitant linguistic preference relation (HLPR), is constructed. The basic elements in the HLPR are hesitant fuzzy linguistic numbers (HFLNs). At first, new operational laws and aggregation operators of HFLNs are defined to overcome the limitations in existing literature. Subsequently, a novel comparison method based on likelihood is proposed to obtain the order relationship of two HFLNs. Then, a likelihood-based consistency index is introduced to represent the difference between two hesitant linguistic preference relations (HLPRs). It is a new way to express the consistency degree for the reason that the traditional consistency indices are almost exclusively based on distance measures. Meanwhile, a consistency-improving model is suggested to attain acceptable consistent HLPRs. In addition, a method to receive reasonable ranking results from HLPRs with acceptable consistency is presented. At last, this method is used to pick out the best mine ventilation system under uncertain linguistic decision conditions. A comparison and a discussion are conducted to demonstrate the validity of the presented approach. The results show that the proposed method is effective for selecting the optimal mine ventilation system, and provides references for the construction and management of mines.

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“…To deal with it, the theory of fuzzy set (FS) [4] or extended fuzzy sets such as intuitionistic fuzzy set (IFS) [5], interval-valued IFS (IVIFS) [6] are the most successful ones, which characterize the criterion values in terms of membership degrees. Since their existence, numerous researchers were paying more attention to these theories and developed several approaches using different aggregation operators [7][8][9][10] and ranking methods [11][12][13] in the processing of the information values.…”

Section: Introductionmentioning

confidence: 99%

Multi-Criteria Decision-Making Method Based on Prioritized Muirhead Mean Aggregation Operator under Neutrosophic Set Environment

Garg

nancy

2018

Symmetry

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Abstract:The aim of this paper is to introduce some new operators for aggregating single-valued neutrosophic (SVN) information and to apply them to solve the multi-criteria decision-making (MCDM) problems. Single-valued neutrosophic set, as an extension and generalization of an intuitionistic fuzzy set, is a powerful tool to describe the fuzziness and uncertainty, and Muirhead mean (MM) is a well-known aggregation operator which can consider interrelationships among any number of arguments assigned by a variable vector. In order to make full use of the advantages of both, we introduce two new prioritized MM aggregation operators, such as the SVN prioritized MM (SVNPMM) and SVN prioritized dual MM (SVNPDMM) under SVN set environment. In addition, some properties of these new aggregation operators are investigated and some special cases are discussed. Furthermore, we propose a new method based on these operators for solving the MCDM problems. Finally, an illustrative example is presented to testify the efficiency and superiority of the proposed method by comparing it with the existing method.

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Fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights

Cited by 119 publications

References 14 publications

Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

Ranking p-norm generalised fuzzy numbers with different left height and right height using integral values

Selecting the Optimal Mine Ventilation System via a Decision Making Framework under Hesitant Linguistic Environment

Multi-Criteria Decision-Making Method Based on Prioritized Muirhead Mean Aggregation Operator under Neutrosophic Set Environment

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