Evaluation of approximate Fuzzy Membership Function using Linguistic Input-an Approached Based on Cubic Spline

  • Stabania Chowdhury Department of Mathematics, Guru Nanak Institute of Technology, Panihati, Kolkata, India (IN)
  • Rahul Kar Department of Mathematics, Springdale High School, Kalyani, Nadia, India (IN)
Keywords: Fuzzy membership function, Defuzzification, Cubic spline formula, Risk factor

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Abstract

Fuzzy logic systems have found extensive use in system identification, decision making, and pattern recognition problems from industries to academics. The membership functions play a pivotal role in overall role in fuzzy representation, as these are considered as the building blocks of fuzzy set theory and they decide the degree of truth in fuzzy logic. The extraction of the membership function is ambience dependent and thus complication exists in the process of evaluation. In this assessment the main work deals with the derivation of fuzzy membership function where numerical data is available. The numerical cubic spline and defuzzification technique are used here. In this paper we mainly used triangular fuzzy number to construct the membership function. A case study is furnished to emphasize the advantage of adopting the method.



Published
2020-11-20
Section
Articles
How to Cite
Stabania Chowdhury, & Kar, R. (2020). Evaluation of approximate Fuzzy Membership Function using Linguistic Input-an Approached Based on Cubic Spline . JINAV: Journal of Information and Visualization, 1(2), 53-59. https://doi.org/10.35877/454RI.jinav215