Multi Q-fuzzy parameterized soft set and its application

Adam, Fatma; Hassan, Nasruddin

doi:10.3233/ifs-131009

Cited by 39 publications

(20 citation statements)

References 12 publications

(9 reference statements)

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“…Currently, the study on soft sets is developing promptly such as fuzzy soft sets [8,9], intuitionistic fuzzy soft sets [10,11] and multi-fuzzy soft sets [12]. Following from there, Alkhazaleh and Salleh [13] investigated the theory of soft expert sets, which later broadened to a fuzzy soft expert set theory [14], a bipolar fuzzy soft expert set [15], a multi Q-fuzzy soft expert set [16], and a neutrosophic soft expert set [17,18].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Parameterized Complex Multi-Fuzzy Soft Expert Set Theory and Its Application in Decision-Making

Al-Qudah

Hassan

2019

Symmetry

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Contemporary research has refined systems with complex fuzzy sets in order to improve the design and model of real-life applications. Symmetry and antisymmetry are basic characteristics of binary relations used when modeling the decision maker’s preferences. A recent focus has been the analysis of a complex data set using the properties of fuzzy concept lattice and the complex soft set. We will introduce a new concept to represent the information which utilizes the time factor, called fuzzy parameterized complex multi-fuzzy soft expert set ( F P - CMFSES ), and investigate part of its fundamental properties. This F P - CMFSES model allows us to validate the information provided by an expert, at a given phase of time, using the properties of complex fuzzy sets. We then construct an algorithm based on this concept by converting it from the complex state to the real state. Eventually, we implement it to a decision-making problem to demonstrate the applicability of the suggested method. A comparison among F P - CMFSES and other existing methods is made to expose the dominance of the suggested method. Apart from that, we also propose the weighted fuzzy parameterized complex multi-fuzzy soft expert set and investigate its application to decision-making.

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Section: Introductionmentioning

confidence: 99%

Fuzzy Parameterized Complex Multi-Fuzzy Soft Expert Set Theory and Its Application in Decision-Making

Al-Qudah

Hassan

2019

Symmetry

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“…Presently, work on soft set theory is progressing rapidly. Various operations and applications of soft sets were developed rapidly, including multi-adjoint t-concept lattices [5], signatures, definitions, operators and applications to fuzzy modelling [6], fuzzy inference system optimized by genetic algorithm for robust face and pose detection [7], fuzzy multi-objective modeling of effectiveness and user experience in online advertising [8], possibility fuzzy soft set [9], soft multiset theory [10], multiparameterized soft set [11], soft intuitionistic fuzzy sets [12], Q-fuzzy soft sets [13][14][15], and multi Q-fuzzy sets [16][17][18], thereby opening avenues to many applications [19,20]. Later, Maji [21] introduced a more generalized concept, which is a combination of neutrosophic sets and soft sets and studied its properties.…”

Section: Introductionmentioning

confidence: 99%

Neutrosophic Soft Expert Multiset and Their Application to Multiple Criteria Decision Making

Bakbak¹,

Uluçay

Şahin

2019

Mathematics

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“…From this point of view, the idea of Q-fuzzy sets was came out. Afterwards, the concept of multi Q-fuzzy soft sets [20][21][22][23][24] was established to combine the key feature of soft sets and Q-fuzzy sets with multi membership values. The notion of multi Q-hesitant fuzzy soft sets is the generalization of multi Q-fuzzy soft sets.…”

Section: Introductionmentioning

confidence: 99%

A Decision-Making Approach Based on a Multi Q-Hesitant Fuzzy Soft Multi-Granulation Rough Model

2018

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In this paper, we propose a new hybrid model, multi Q-hesitant fuzzy soft multi-granulation rough set model, by combining a multi Q-hesitant fuzzy soft set and multi-granulation rough set. We demonstrate some useful properties of these multi Q-hesitant fuzzy soft multi-granulation rough sets. Furthermore, we define multi Q-hesitant fuzzy soft ( M k Q H F S ) rough approximation operators in terms of M k Q H F S relations and M k Q H F S multi-granulation rough approximation operators in terms of M k Q H F S relations. We study the main properties of lower and upper M k Q H F S rough approximation operators and lower and upper M k Q H F S multi-granulation rough approximation operators. Moreover, we develop a general framework for dealing with uncertainty in decision-making by using the multi Q-hesitant fuzzy soft multi-granulation rough sets. We analyze the photovoltaic systems fault detection to show the proposed decision methodology.

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Multi Q-fuzzy parameterized soft set and its application

Cited by 39 publications

References 12 publications

Fuzzy Parameterized Complex Multi-Fuzzy Soft Expert Set Theory and Its Application in Decision-Making

Fuzzy Parameterized Complex Multi-Fuzzy Soft Expert Set Theory and Its Application in Decision-Making

Neutrosophic Soft Expert Multiset and Their Application to Multiple Criteria Decision Making

A Decision-Making Approach Based on a Multi Q-Hesitant Fuzzy Soft Multi-Granulation Rough Model

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