Career selection of students using hybridized distance measure based on picture fuzzy set and rough set theory

Sahu, Rekha; Dash, Satya Ranjan; Das, Sujit

doi:10.31181/dmame2104104s

Cited by 85 publications

(51 citation statements)

References 35 publications

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“…It is used in most cases where the study involves dealing with imprecise or incomplete information [ 38 ]. For instance, this method has been used successfully for supplier selection [ 39 ], career path selection for students [ 40 ], parametric analysis for the machining process [ 41 ] and so on. The reason rough TOPSIS is often preferred in much recent research is that it not only improves the reliability of the TOPSIS calculation program but also expresses more potential information considering the uncertainties [ 36 , 42 ],.The proposed rough TOPSIS based on flexible FMEA evaluates the failure modes except for prior information and made the execution of the FMEA process very effective [ 43 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluating factors contributing to the failure of information system in the banking industry

et al. 2022

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The increasing use of Information Technology (IT) has led to many security and other related failures in the banks and other financial institutions in Bangladesh. In this paper, we investigated the factors contributing to the failurein the IT system of the banking industry in Bangladesh. Based on the experts’ opinions and weight on the specified evaluating criteria, an empirical test was conducted using a rough set theory to produce a framework for the IT system failure factors. In this study, an extended approach involving the integration of rough set theory based flexible Failure Mode and Effect Analysis (FMEA) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) has beenapplied to help the managers of the corresponding field to identify the factors responsible for the failure of the IT system in the banking industries and then prioritize them accordingly, for the ease of decision-making.In this research, eleven such failure factors were identified, which were then quantitatively analyzed to facilitate managers in crucial decision-making. It was observed that cyber-attack, database hack risks, server failure, network interruption, broadcast data error, and virus effect were the most significant factors for the failure of the IT system. The framework developed in this research can be utilized to assist in efficient decision-makingin other serviceindustries where IT systems play a key role. To the best of the knowledge, this is the first study thatempirically tested key failure factors of the IT system for the banking sector using an integrated method.

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Section: Introductionmentioning

confidence: 99%

Evaluating factors contributing to the failure of information system in the banking industry

et al. 2022

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“…Riaz et al [75] introduced various interesting properties of topological structure on soft multi-sets and their applications in MCDM. Sahu et al [76] developed a career selection picture fuzzy set and rough set theory method for students with hybridized distance measure measures. Ali et al [77] introduced Einstein geometric aggregation operators using a novel complex interval-valued pythagorean fuzzy setting.…”

Section: Introduction An Literature Reviewmentioning

confidence: 99%

Spherical Linear Diophantine Fuzzy Soft Rough Sets with Multi-Criteria Decision Making

Hashmi

Tehrim

Riaz

et al. 2021

Axioms

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Modeling uncertainties with spherical linear Diophantine fuzzy sets (SLDFSs) is a robust approach towards engineering, information management, medicine, multi-criteria decision-making (MCDM) applications. The existing concepts of neutrosophic sets (NSs), picture fuzzy sets (PFSs), and spherical fuzzy sets (SFSs) are strong models for MCDM. Nevertheless, these models have certain limitations for three indexes, satisfaction (membership), dissatisfaction (non-membership), refusal/abstain (indeterminacy) grades. A SLDFS with the use of reference parameters becomes an advanced approach to deal with uncertainties in MCDM and to remove strict limitations of above grades. In this approach the decision makers (DMs) have the freedom for the selection of above three indexes in [0,1]. The addition of reference parameters with three index/grades is a more effective approach to analyze DMs opinion. We discuss the concept of spherical linear Diophantine fuzzy numbers (SLDFNs) and certain properties of SLDFSs and SLDFNs. These concepts are illustrated by examples and graphical representation. Some score functions for comparison of LDFNs are developed. We introduce the novel concepts of spherical linear Diophantine fuzzy soft rough set (SLDFSRS) and spherical linear Diophantine fuzzy soft approximation space. The proposed model of SLDFSRS is a robust hybrid model of SLDFS, soft set, and rough set. We develop new algorithms for MCDM of suitable clean energy technology. We use the concepts of score functions, reduct, and core for the optimal decision. A brief comparative analysis of the proposed approach with some existing techniques is established to indicate the validity, flexibility, and superiority of the suggested MCDM approach.

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“…With a different perspective, Sahu et al [13] utilized a hybridized distance measure based on the theories of PFSs and rough sets for the career selection of students. For more important terminologies related to PFSs, the readers may refer to [14][15][16][17][18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

A New Group Decision-Making Technique under Picture Fuzzy Soft Expert Information

Tchier

Ali

Gulzar

et al. 2021

Entropy

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As an extension of intuitionistic fuzzy sets, the theory of picture fuzzy sets not only deals with the degrees of rejection and acceptance but also considers the degree of refusal during a decision-making process; therefore, by incorporating this competency of picture fuzzy sets, the goal of this study is to propose a novel hybrid model called picture fuzzy soft expert sets by combining picture fuzzy sets with soft expert sets for dealing with uncertainties in different real-world group decision-making problems. The proposed hybrid model is a more generalized form of intuitionistic fuzzy soft expert sets. Some novel desirable properties of the proposed model, namely, subset, equality, complement, union and intersection, are investigated together with their corresponding examples. Two well-known operations AND and OR are also studied for the developed model. Further, a decision-making method supporting by an algorithmic format under the proposed approach is presented. Moreover, an illustrative application is provided for its better demonstration, which is subjected to the selection of a suitable company of virtual reality devices. Finally, a comparison of the initiated method is explored with some existing models, including intuitionistic fuzzy soft expert sets.

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Career selection of students using hybridized distance measure based on picture fuzzy set and rough set theory

Cited by 85 publications

References 35 publications

Evaluating factors contributing to the failure of information system in the banking industry

Evaluating factors contributing to the failure of information system in the banking industry

Spherical Linear Diophantine Fuzzy Soft Rough Sets with Multi-Criteria Decision Making

A New Group Decision-Making Technique under Picture Fuzzy Soft Expert Information

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