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Blockchain knowledge selection under the trapezoidal fermatean fuzzy number.

Aliya Fahmi1, Zahida Maqbool2, Fazli Amin3

  • 1Department of Mathematics, The University of Faisalabad, Faisalabad, Pakistan.

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|November 21, 2022
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Summary

This study introduces a new trapezoidal fermatean fuzzy model to improve multi-attribute group decision-making (MAGDM) for blockchain knowledge assessment. The novel framework enhances decision accuracy and robustness in complex financial scenarios.

Keywords:
Aggregation operatorsBlockchain knowledgeMulti-attribute decision makingTrapezoidal fermatean fuzzy TOPSIS techniqueTrapezoidal fuzzy set

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Area of Science:

  • Decision Sciences
  • Computer Science
  • Financial Technology

Background:

  • Blockchain technology is crucial for secure financial transmittals, but coordinating diverse opinions under uncertainty in group decision-making remains a challenge.
  • Existing multi-attribute group decision-making (MAGDM) models struggle with the inherent uncertainties in real-world financial applications involving blockchain knowledge.

Purpose of the Study:

  • To introduce a generalized framework for MAGDM problems, specifically addressing uncertainties in blockchain knowledge assessment.
  • To develop and apply a novel trapezoidal fermatean fuzzy set model for more flexible and descriptive representation of decision-maker attitudes.

Main Methods:

  • Introduced trapezoidal fermatean fuzzy sets, generalizing existing fuzzy set theories.
  • Defined operational laws and an Einstein aggregation operator for trapezoidal fermatean fuzzy numbers.
  • Integrated the trapezoidal fermatean fuzzy set approach with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for MAGDM.

Main Results:

  • Developed an integrated trapezoidal fermatean fuzzy-TOPSIS framework for MAGDM.
  • The framework effectively identifies subjective attribute weights and ranks alternatives in blockchain knowledge assessment.
  • Case study demonstrated the proposed method's feasibility, effectiveness, robustness, and superiority through sensitivity and comparison analyses.

Conclusions:

  • The proposed trapezoidal fermatean fuzzy-TOPSIS framework offers a robust and effective solution for MAGDM problems involving blockchain knowledge.
  • The model's ability to handle uncertainty and linguistic terms enhances decision-making accuracy in complex financial and blockchain-related scenarios.