On the Temperature Indices of Fuzzy Graphs and its Application forQSPR analysis on Autism drugs

Authors

  • Mahsa Sadeghi * Department of Mathematics, University of Mazandaran, Babolsar, Iran.
  • Ali Asghar Talebi Department of Mathematics, University of Mazandaran, Babolsar, Iran.
  • Jaber Ramezani Department of Mathematics, University of Mazandaran, Babolsar, Iran.

https://doi.org/10.48314/ramd.vi.71

Abstract

In this work, we introduce the concept of fuzzy temperature indices and rigorously compute them for
fundamental fuzzy graph structures as well as their standard operators, including Cartesian products and
compositions. Utilizing a graph-theoretical modeling approach, fuzzy graphs are constructed for a selection
of pharmaceutical compounds commonly prescribed for Autism Spectrum Disorders (ASD), specifically
Aripiprazole, Haloperidol, Risperidone, Sertraline, Venlafaxine, and Ziprasidone. The fuzzy temperature
indices are then derived based on the underlying physicochemical descriptors of these compounds. Linear
regression analyses are performed to explore the predictive capacity of the fuzzy topological indices in
relation to drug properties. The findings highlight the significance of fuzzy temperature indices as robust
mathematical invariants, providing valuable insights into the structural and functional profiling of ASD
medications, and opening new avenues for the application of fuzzy graph theory in pharmaceutical sciences
and computational drug design.

Keywords:

Temperature indices, Fuzzy graph, Autism drugs, QSPR analysis

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Published

2025-09-17

Issue

Articles in Press

Section

Articles

How to Cite

Sadeghi, M. ., Talebi, A. A., & Ramezani, J. (2025). On the Temperature Indices of Fuzzy Graphs and its Application forQSPR analysis on Autism drugs. Risk Assessment and Management Decisions. https://doi.org/10.48314/ramd.vi.71