Interval type-3 fuzzy fractal approach in sound speaker quality control evaluation. (November 2022)

• Record Type: Journal Article
• Authors: Castillo, Oscar; Castro, Juan R.; Melin, Patricia
• Is Part Of: Engineering applications of artificial intelligence. Volume 116(2022)
• Publication Date: 2022-11
• Subjects: Type-3 fuzzy logic -- Type-2 fuzzy logic -- Speaker quality; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2022.105363
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: This article is presenting a proposal for the mathematical definition of interval type-3 fuzzy sets, as a basis for later constructing all the theory needed for building interval type-3 fuzzy systems for different areas of application. It is well known that the most used form of fuzzy logic is the one called type-1, which later evolved into interval and general type-2. Recently, we have seen that type-2 fuzzy has outperformed type-1 in many real problems when there is high level of uncertainty, dynamic situations or nonlinearity. For these reasons it is worthwhile to explore the new area of type-3 fuzzy logic, and in this paper, we are putting forward some mathematical definitions of type-3 fuzzy sets and systems, as a starting point for later proposing their applications. In addition, we illustrate the potential of interval type-3 in a decision-making application in quality control. The aim of this study is to show the advantages of type-3 in a quality control problem that can be viewed as a decision-making process under uncertainty that estimates product quality Speaker manufacturing requires strict quality control and a combination of type-3 with fractal theory is able to outperform previous works with type-2 and type-1 in quality control. Simulation results of the proposed approach are compared with the results provided by human experts in sound speaker quality control to validate the effectiveness of the type-3 fuzzy fractal method in handling the uncertainty of this problem.