Geometric Approach for Solving First Order Non-Homogenous Fuzzy Difference Equation

Authors

  • Abdul Alamin Department of Applied Mathematics, Maulana Abul Kalam Azad University of Technology, West Bengal, Haringhata 741249, West Bengal, India Author https://orcid.org/0009-0009-9621-5383
  • Mostafijur Rahaman Department of Mathematics School of Liberal Arts & Sciences, Mohan Babu University, Tirupati, 517102, Andhra Pradesh, India Author https://orcid.org/0000-0002-5513-4095
  • Sankar Prasad Mondal Department of Applied Mathematics, Maulana Abul Kalam Azad University of Technology, West Bengal, Haringhata 741249, West Bengal, India Author https://orcid.org/0000-0003-4690-2598

DOI:

https://doi.org/10.31181/sor2120257

Keywords:

Fuzzy difference, Hukuhara difference, Geometric method, Mathematical modeling

Abstract

Real-life scenario modeling with mathematics is very important nowadays. Depending upon system behavior, it may also model discrete systems in several cases. In discrete system modeling, the difference equation is one of the well-known methodologies. However, if some uncertain factors are involved in the discrete models, then uncertain difference equation concepts come into play. The fuzzy difference equation is one of them. The fuzzy difference equation is significant as it can represent variances of dependent variables in a discrete frame under uncertainty. In this paper, a first-order non-homogenous linear difference equation is considered under fuzzy uncertainty, a special kind of fuzzy difference equation. Here, a well-known fuzzy geometric approach is utilized to solve the mentioned first-order non-homogeneous fuzzy difference equation. An application, namely a fuzzy prescription for digoxin based on the fuzzy initial valued problem, is also discussed in numerical illustrations as a consequence of the proposed theory.

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Published

2025-01-01

How to Cite

Alamin, A., Rahaman, M., & Mondal, S. P. (2025). Geometric Approach for Solving First Order Non-Homogenous Fuzzy Difference Equation. Spectrum of Operational Research, 2(1), 61-71. https://doi.org/10.31181/sor2120257