Eigen Spherical Fuzzy Set and its Application in Decision Making Problem

Guleria, Abhishek; Bajaj, Rakesh Kumar

doi:10.24200/sci.2019.51999.2470

Cited by 5 publications

(3 citation statements)

References 36 publications

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“…In SFS, the sum of the square of MG, AG, and non-MG ranges in the unit interval [0,1]. Guleria and Bajaj [35] used the concept of SFS in the problem of decision making. Ali et al [36] discussed the complex spherical fuzzy set (CSFS).…”

Section: Introductionmentioning

confidence: 99%

A new approach to investigate the effects of artificial neural networks based on bipolar complex spherical fuzzy information

Gwak

Garg

Jan

et al. 2023

Complex Intell. Syst.

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Artificial neural network is revolutionizing business and everyday life, bringing us to the next level in artificial intelligence. It has a unique ability to extract meaning from complex data to find patterns and detect trends that are too convoluted for the human brain. This paper analyzes the artificial neural network impact on different computational organizations by using the innovative structure of bipolar complex spherical fuzzy relation which is any subset of the Cartesian product of two bipolar complex spherical fuzzy sets. This notion has a comprehensive structure that consists of membership grade, abstinence grade, and non-membership grade. Furthermore, various kinds of bipolar complex spherical fuzzy relation with suitable examples are given and some authentic results also have been proved. These newly defined structures are used to investigate the impact of artificial neural network work on a variety of organizations. The innovative framework is also compared with the existing structure in the field of fuzzy set theory to prove its superiority.

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Section: Introductionmentioning

confidence: 99%

A new approach to investigate the effects of artificial neural networks based on bipolar complex spherical fuzzy information

Gwak

Garg

Jan

et al. 2023

Complex Intell. Syst.

View full text Add to dashboard Cite

show abstract

“…Sometimes existing mathematical models are insufficient to deal with such situations, and therefore new models are developed. Zadeh [1] proposed fuzzy sets as a powerful and effective approach for modeling uncertainty, and in the following years, the general forms of these sets were studied (e.g., [2][3][4][5][6]). In 1999, Molodtsov [7] initiated the theory of soft set to parametrically classify objects (or elements of the universe) in uncertain environments.…”

Section: Introductionmentioning

confidence: 99%

Decompositions of soft sets and soft matrices with applications in group decision making

Atagün

Kamacı

2021

Scientia Iranica

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The decompositions of soft sets and soft matrices are important tools for theoretical and practical studies. In this paper, firstly, we study the decomposition of soft sets in detail. Later, we introduce the concepts of αupper, α-lower, α-intersection and α-union for soft matrices and present some decomposition theorems. Some of these operations are set-restricted types of existing operations of soft sets/matrices, others are α-oriented operations that provide functionality in some cases. Moreover, some relations of decompositions of soft sets and soft matrices are investigated and the newfound relations are supported with numerical examples. Finally, two new group decision making algorithms based on soft sets/matrices are constructed, and then their efficiency and practicality are demonstrated by dealing with real life problems and comparison analysis. By using these proposed approaches, solutions can be presented to soft set-based multi-criteria decision making problems, both ordinary and involving primary assessments. These allow to handle soft set-based multi-criteria decision making from different perspectives.

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“…Recently, Jin et al [10] introduced the notion of linguistic spherical fuzzy set (LSFS) and investigated its various aggregation operators to develop a new approach to solve the decision-making problems. Also, Guleria and Bajaj [11] presented eigen spherical fuzzy sets with an algorithm to find the greatest and the least eigen spherical fuzzy sets to solve some of the decision-making problems.…”

Section: Introductionmentioning

confidence: 99%

T-spherical Fuzzy Soft Matrices with Applications in Decision Making and Selection Process

Bajaj

Guleria

2021

Scientia Iranica

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In the present communication, we have introduced the notion of T -spherical fuzzy soft matrix (TSFSM) and studied various types of associated binary operations and properties. In literature, it has been observed that the concept of soft matrix plays a vital role in many engineering applications as well as to cater different socio-economic and financial sector problems. As per the definition of T -spherical fuzzy set, the proposed notion would have an additional capability to address the impreciseness of the information close enough to human opinion mathematically. Further, on the basis of the structure of proposed TSFSM and using the concept of choice matrix along with its weighted form, a new algorithm for the decision-making process has been outlined. Next, utilizing the score/utility matrix, we present another algorithm for the selection process. For the sake of understanding of the proposed methodologies, illustrative examples have also been presented. Some comparative remarks for the proposed techniques in contrast with existing techniques have been listed for a better readability and understanding.

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Eigen Spherical Fuzzy Set and its Application in Decision Making Problem

Cited by 5 publications

References 36 publications

A new approach to investigate the effects of artificial neural networks based on bipolar complex spherical fuzzy information

A new approach to investigate the effects of artificial neural networks based on bipolar complex spherical fuzzy information

Decompositions of soft sets and soft matrices with applications in group decision making

T-spherical Fuzzy Soft Matrices with Applications in Decision Making and Selection Process

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