This paper proposes an intuitionistic fuzzy optimization approach to solve a multi-objective nonlinear programming problem in the context of a reliability application. We have considered a multi-objective reliability optimization problem with reliability and cost as objective functions. Intuitionistic fuzzy optimization approach is used to solve this multi-objective reliability optimization mod...

this paper focuses on the non-fragile guaranteed cost control problem for a class of t-s fuzzy time-varying delay systems with local bilinear models. the objective is to design a non-fragile guaranteed cost state feedback controller via the parallel distributed compensation (pdc) approach such that the closed-loop system is delay-dependent asymptotically stable and the closed-loop performance i...

An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transport...

In this paper we present an approach to neuro{fuzzy classiication that is able to learn fuzzy sets and fuzzy rules from data. The fuzzy rules that are created by this approach can be very well interpreted, however, they do not classify as good as the rules derived by sophisticated fuzzy clustering algorithms. They on the other hand supply usually unsatisfying fuzzy sets what makes it hard to in...

The paper presents second author’s step toward building quite new theory of fuzzy signals. Before, in the first step author defined fuzzy Fourier transform. Here, an approach to description of fuzzy correlation functions is proposed. New definitions, called later fuzzy correlation and defuzzified correlation are proposed for fuzzy signals. The definitions are based on new concepts of the class ...

In this chapter we focus on the Wisconsin breast cancer diagnosis (WBCD) problem, combining two methodologies—fuzzy systems and evolutionary algorithms—to automatically produce diagnostic systems. We present two hybrid approaches: (1) a fuzzy-genetic algorithm, and (2) Fuzzy CoCo, a novel cooperative coevolutionary approach to fuzzy modeling. Both methods produce systems exhibiting high classif...

One of the challenges in information retrieval is providing accurate answers to a user’s question often expressed as uncertainty words. Most answers are based on a Syntactic approach rather than a Semantic analysis of the query. In this paper our objective is to present a hybrid approach for a Semantic question answering retrieval system using Ontology Similarity and Fuzzy logic. We use a Fuzzy...

To deal with system uncertainty, finite automata have been generalized into fuzzy automata. Stamenkovic and Ciric proposed an approach using the position automata for the construction of fuzzy automata from fuzzy regular expressions. There exist multifarious methodologies for the construction of finite automata from regular expressions known as Thompson construction, Antimirov partial derivativ...

Abstract-This paper presents a general approach to fuzzy clustering methods. A generalised fuzzy objective function is used to combine fuzzy c-means clustering, fuzzy entropy clustering, and their extended versions into a generalised fuzzy clustering method. Some new extended versions of the above-mentioned clustering methods are proposed from this general approach. Several cluster data sets we...

Six Sigma is a strategy for achieving process improvement and operational excellence within an organization. Decisions on critical parameter selection in analysis phase are always very crucial; it plays a primary role in successful execution of Six Sigma project and for productivity improvement in manufacturing environment and involves the imprecise, vague and uncertain information. Using a cas...