Fuzzy score and fuzzy cost SuperHyperFunction

Authors

  • Takaaki Fujita Independent Researcher (not affiliated with any university or research institute), Tokyo, Japan
  • Arif Mehmood Department of Mathematics, Institute of Numerical Sciences, Gomal University, Pakistan

DOI:

https://doi.org/10.31181/jdaic10030112025f

Keywords:

fuzzy function, fuzzy score function, fuzzy cost function

Abstract

A HyperFunction associates each input with a set of admissible outputs, extending conventional functions by allowing multi-valued rather than single-valued mappings. A SuperHyperFunction further generalizes this concept by employing iterated powersets for both its domain and codomain, enabling the representation of hierarchical, multi-level output structures and HyperStructural multi-valued behavior within complex systems. Although HyperFunctions and SuperHyperFunctions offer expressive tools for modeling hierarchical functional relationships, their study in the existing literature remains relatively limited. This paper extends the fuzzy score function and fuzzy cost function within the frameworks of HyperFunctions and SuperHyperFunctions and provides a concise theoretical analysis of their essential properties.

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Published

30.11.2025

How to Cite

Fujita, T., & Mehmood, A. (2025). Fuzzy score and fuzzy cost SuperHyperFunction. Journal of Decision Analytics and Intelligent Computing, 5(1), 219–228. https://doi.org/10.31181/jdaic10030112025f