Some Logarithmic Intuitionistic Fuzzy Einstein Aggregation Operators under Confidence Level

Rahman, Khaista; Hezam, Ibrahim M.; Božanić, Darko; Puška, Adis; Milovančević, Miloš

doi:10.3390/pr11041298

Cited by 5 publications

(4 citation statements)

References 40 publications

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“…Rahman et al introduced some new logarithm operational laws for intuitionistic fuzzy sets and developed some structure properties with more effectiveness compared with the existing methods from the comparison and sensitivity analysis [31].…”

Section: Constrain Conditionsmentioning

confidence: 99%

Progress of Optimization in Manufacturing Industries and Energy System

Zhang,

Yang,

You

2024

Processes

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Section: Constrain Conditionsmentioning

confidence: 99%

Progress of Optimization in Manufacturing Industries and Energy System

Zhang,

Yang,

You

2024

Processes

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“…This paper draws inspiration from three separate ideas introduced in previous studies: the logarithmic concept [23][24][25][26], the confidence concept [29], and the induced concept [30][31][32][33]. Despite their relevance and potential synergies, prior research has, surprisingly, not attempted to integrate these three concepts.…”

Section: Motivationmentioning

confidence: 99%

“…This approach enhances the decision-making process by providing a balanced and nuanced perspective, taking into account the varying degrees of importance assigned to different elements. Rahman [23], Li and Wei [24], Rahman et al [25], and Qiyas et al [26], presented logarithmic techniques, namely LIFWAA, LIFOWAA, LIFEWAA, LIFEOWAA, LIFEHAA, LIFEWGA, LIFEOWGA, LIFEHGA, LIFWGA, LIFOWGA, CLIFEWGA, CLIFEOWGA, CLIFEHGA, CLIFEWAA, CLIFEOWAA, CLIFEHAA, LCWAA, LCOWAA, LCWGA, LCOWGA operators. These methods offer significant value in tackling certain decision-making problems.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Detection of Soybean Leaf Diseases Using an Improved Yolov5 Model

Peng,

Xi,

Wei

et al. 2024

IJKIS

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“… Wei et al (2022) , Pinar, Babak Daneshvar & Özdemir (2021) and Krishankumar et al (2021) proposed AOs for different extensions of fuzzy sets and their applications towards vendor selection. Some extensive work related to MADM can be seen in Wan, Jiuying & Deyan (2015) , Dong & Wan (2016) , Puška et al (2023) , Rahman et al (2023) , Riaz & Farid (2023) , Kausar, Riaz & Farid (2023) . Finally, some existing AOs related to different extensions of FSs are given in Table 1 .…”

Section: Literature Reviewmentioning

confidence: 99%

A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregation

Riaz,

Farid,

Razzaq

et al. 2023

PeerJ Computer Science

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In recent years, as corporate consciousness of environmental preservation and sustainable growth has increased, the importance of sustainability marketing in the logistic process has grown. Both academics and business have increased their focus on sustainable logistics procedures. As the body of literature expands, expanding the field’s knowledge requires establishing new avenues by analyzing past research critically and identifying future prospects. The concept of “q-rung orthopair fuzzy soft set” (q-ROFSS) is a new hybrid model of a q-rung orthopair fuzzy set (q-ROFS) and soft set (SS). A q-ROFSS is a novel approach to address uncertain information in terms of generalized membership grades in a broader space. The basic alluring characteristic of q-ROFS is that they provide a broader space for membership and non-membership grades whereas SS is a robust approach to address uncertain information. These models play a vital role in various fields such as decision analysis, information analysis, computational intelligence, and artificial intelligence. The main objective of this article is to construct new aggregation operators (AOs) named “q-rung orthopair fuzzy soft prioritized weighted averaging” (q-ROFSPWA) operator and “q-rung orthopair fuzzy soft prioritized weighted geometric” (q-ROFSPWG) operator for the fusion of a group of q-rung orthopair fuzzy soft numbers and to tackle complexities and difficulties in existing operators. These AOs provide more effective information fusion tools for uncertain multi-attribute decision-making problems. Additionally, it was shown that the proposed AOs have a higher power of discriminating and are less sensitive to noise when it comes to evaluating the performances of sustainable logistic providers.

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Some Logarithmic Intuitionistic Fuzzy Einstein Aggregation Operators under Confidence Level

Cited by 5 publications

References 40 publications

Progress of Optimization in Manufacturing Industries and Energy System

Progress of Optimization in Manufacturing Industries and Energy System

Enhanced Detection of Soybean Leaf Diseases Using an Improved Yolov5 Model

A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregation

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