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Evaluating Pancreatic Cancer Treatment Strategies Using a Novel Polytopic Fuzzy Tensor Approach.

Muhammad Bilal1, Chaoqian Li1, A K Alzahrani2

  • 1School of Mathematics and Statistics, Yunnan University, Kunming 650106, China.

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Summary
This summary is machine-generated.

This study introduces a novel polytopic fuzzy tensor (PFT) model for complex decision-making. The PFT framework handles imprecise data, offering more reliable outcomes than traditional fuzzy methods.

Keywords:
Polytopic Fuzzy Setcancer treatmentdecision makingfuzzy setpolytopic fuzzy tensor

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Area of Science:

  • Decision Science
  • Fuzzy Mathematics
  • Computational Intelligence

Background:

  • Real-world decision-making is increasingly complex and uncertain.
  • Traditional methods struggle with high-dimensional, imprecise, and ambiguous information.

Purpose of the Study:

  • Introduce a novel polytopic fuzzy tensor (PFT) framework.
  • Address challenges in multi-criteria group decision-making under uncertainty.

Main Methods:

  • Developed a PFT model unifying polytope geometry and fuzzy tensors.
  • Defined algebraic operations, aggregation mechanisms, and theoretical properties for PFT.
  • Validated the framework with mathematical formulations.

Main Results:

  • Demonstrated PFT effectiveness in evaluating pancreatic cancer treatments.
  • PFT outperformed traditional fuzzy techniques in consistency and reliability.
  • Showcased superior handling of multidimensional expert evaluations and conflicting information.

Conclusions:

  • The PFT model offers a flexible, theoretically sound, and practical tool for complex decisions.
  • This research advances fuzzy decision science.
  • Future work includes computational optimization and real-time data adaptation.