Choquet Integral-Based Aczel–Alsina Aggregation Operators for Interval-Valued Intuitionistic Fuzzy Information and Their Application to Human Activity Recognition

Garg, Harish; Tehreem,; Nguyen, Gia Nhu; Alballa, Tmader; Khalifa, Hamiden Abd El-Wahed

doi:10.3390/sym15071438

Cited by 5 publications

(1 citation statement)

References 58 publications

(82 reference statements)

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“…Wang et al 42 utilized Aczel–Alsina based Hamy-Mean AOs for T-spherical fuzzy MCDM. Some other contributions include 43 – 45 . Considering this efficiency and applicability of Aczel–Alsina TN and TCoN, and the need for multi-polar fuzzy aggregation, this work focuses on the development of m F set-based Aczel–Alsina AOs.…”

Section: Introductionmentioning

confidence: 99%

Identification of desalination and wind power plants sites using m-polar fuzzy Aczel–Alsina aggregation information

Rahman,

Ali,

Asif

et al. 2024

Sci Rep

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Real-world decision-making problems often include multi-polar uncertainties dependent on multi-dimensional attributes. The m-polar fuzzy (mF) sets can efficiently handle such multi-faceted complications with T-norm based weighted aggregation techniques. The Aczel–Alsina T-norms offer comparatively flexible and accurate aggregation than the other well-known T-norm families. Consequently, this work introduced novel mF Aczel–Alsina aggregation operators (AOs), including weighted averaging (mFAAWA, mFAAOWA, mFAAHWA) and weighted geometric (mFAAWG, mFAAOWG, mFAAHWG) AOs. The fundamental properties, including boundedness, idempotency, monotonicity, and commutativity are investigated. Based on the proposed AOs, a decision-making algorithm is developed and implemented to solve two detailed multi-polar site selection problems (for desalination plant and for wind-power plant). Finally, a comparison with mF Dombi and mF Yager AOs reveals that different T-norm based AOs may yeild different solutions for the same problem.

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Section: Introductionmentioning

confidence: 99%

Identification of desalination and wind power plants sites using m-polar fuzzy Aczel–Alsina aggregation information

Rahman,

Ali,

Asif

et al. 2024

Sci Rep

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Decision Algorithm With Interval-Valued Intuitionistic Fuzzy Hamy Mean Aggregation Operators for Assessment of Agricultural Education Practice

Xiong,

Abbas,

Hussain

et al. 2024

IEEE Access

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The assessment of performance in agricultural education practice is an important issue because it concerns the quality and effectiveness of agricultural education. This evaluation requires effective assessment methods. Interval-valued intuitionistic fuzzy set (IVIFS) is a powerful extension of fuzzy sets and intuitionistic fuzzy sets, conceived to handle uncertainty and vagueness more effectively in assessment performance of agricultural education practice. A comprehensive exploration of interval-valued intuitionistic fuzzy (IVIF) information offers some flexible methods for assessment performance of agricultural education practice. This article identifies the relationship among input arguments with the help of Hamy mean aggregation models. In order to avail smooth approximated results during the aggregation process, some prominent operations of Aczel Alsina aggregation operators are also adopted in the light of an IVIF theory. The robustness of this article is to develop a family of new mathematical strategies based on IVIF information namely IVIF Hamy mean (IVIFHM), IVIF weighted Hamy mean (IVIFWHM), IVIF Dual Hamy mean (IVIFDHM) and IVIF weighted Dual Hamy mean (IVIFWDHM) operators. Some dominant properties of diagnosed aggregation operators are also discussed to show their validity and effectiveness. Moreover, the decision algorithm of the multi-attribute decision-making (MAMD) problem is also adopted to reveal the versatility and adaptability of IVIF contexts. To showcase the practicability of derived approaches, a case study of assessment performance of agricultural education practice is also illustrated. The advantages and supremacy of invented research work are verified with a comparative study of prevailing research work that exists in the literature.INDEX TERMS Interval-valued intuitionistic fuzzy values, Aczel Alsina t-norms and t-conorms, agricultural education practice, and decision support system.

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Selection of safety equipment with choquet integral operators and q-rung orthopair fuzzy information

Hussain,

Zhang,

Ullah

et al. 2024

IFS

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The q-rung orthopair fuzzy set (q-ROFS) is a moderate mathematical model, that has diverse capabilities to handle uncertain and ambiguous information of human opinion during the decision analysis process. The Aczel Alsina operations are more flexible and valuable aggregating tools with parameter values ϻ ⩾ 1, reflecting smooth and accurate information by aggregating awkward and redundant information. The theory of the Choquet integral operator is also used to express the interaction between preferences or criteria by incorporating certain values of preferences. The primary features of this article are to derive some dominant mathematical approaches by combining two different theories like Choquet integral operators and operations of Aczel Alsina tools namely “q-rung orthopair fuzzy Choquet integral Aczel Alsina average” (q-ROFCIAAA), and “q-rung orthopair fuzzy Choquet integral Aczel Alsina geometric” (q-ROFCIAAG) operators. Some special cases and notable characteristics are also demonstrated to show the feasibility of derived approaches. Based on our derived aggregation approaches, a multi-attribute decision-making (MADM) technique aggregates redundant and unpredictable information. In light of developed approaches, a numerical example study to evaluate suitable safety equipment in the construction sector. To reveal the intensity and applicability of derived approaches by contrasting the results of prevailing approaches with currently developed AOs.

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Choquet Integral-Based Aczel–Alsina Aggregation Operators for Interval-Valued Intuitionistic Fuzzy Information and Their Application to Human Activity Recognition

Cited by 5 publications

References 58 publications

Identification of desalination and wind power plants sites using m-polar fuzzy Aczel–Alsina aggregation information

Identification of desalination and wind power plants sites using m-polar fuzzy Aczel–Alsina aggregation information

Decision Algorithm With Interval-Valued Intuitionistic Fuzzy Hamy Mean Aggregation Operators for Assessment of Agricultural Education Practice

Selection of safety equipment with choquet integral operators and q-rung orthopair fuzzy information

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