Title: Type-n fuzzy logic - the next level of type-1 and type-2 fuzzy logic

Authors: Saikat Maity; Sanjay Chakraborty; Saroj Kumar Pandey; Indrajit De; Sourasish Nath

Addresses: Department of Computer Science and Engineering, Sister Nivedita University, Kolkata, India ' Department of Computer Science and Engineering, Techno International New Town, Kolkata, India ' Department of Computer Engineering and Applications, GLA University, Mathura, India ' Department of Computer Science and Engineering, Institute of Engineering and Management, Kolkata, India ' Department of Computer Science and Engineering, JIS University, Kolkata, India

Abstract: The level of uncertainty in a system can be reduced by using type-2 fuzzy logic, which has a superior ability to handle linguistic uncertainties by modelling ambiguity and unreliability of information. Unfortunately, type-2 fuzzy sets are harder to use and understand than type-1 fuzzy sets. This article provides a comprehensive idea on non-stationary fuzzy inference system (FIS) as well as a generalised approach to the extended type-2 fuzzy approach. A new proposed breakdown of T2FS along with stationary and non-stationary fuzzy sets (FIS) is also described using the fuzzy inference system in this article. Besides that, it describes a new generalised FIS technique and ends with a generalised computation of the centroid of a type-2 fuzzy system. A new proposed breakdown of T2FS along with stationary and non-stationary fuzzy sets (FIS) is also described using the fuzzy inference system in this article.

Keywords: fuzzy sets; type-2; decomposition; non-stationary fuzzy sets; fuzzy logic.

DOI: 10.1504/IJIEI.2023.136106

International Journal of Intelligent Engineering Informatics, 2023 Vol.11 No.4, pp.353 - 389

Received: 24 Apr 2023
Accepted: 17 Jul 2023
Published online: 16 Jan 2024 *

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