This paper describes a method for formal compression of fuzzy systems. This method compresses a fuzzy system with an arbitrarily large number of rules into a smaller fuzzy system by removing the redundancy in the fuzzy rule base. As a result of this compression, the number of on-line operations during the fuzzy inference process is significantly reduced without compromising the solution. This r...

Fuzzy techniques may be used to represent uncertainty in both data and knowledge, and fuzzy inference systems (FISs) may be used to reason with such uncertain data and knowledge. In this paper, definitions are first provided for conventional type-1 fuzzy sets, more complex type-2 fuzzy sets and the recently introduced non-stationary fuzzy sets. Two medical applications in which such fuzzy sets ...

This paper describes the optimization of an integration block within the proposed navigation control system for a mobile robot. The control blocks that the integrator will combine are two Fuzzy Inference Systems (FIS) in charge of tracking and reaction control, respectively. The integrator block is called a Weighted Fuzzy Inference System (WFIS) and assigns weigh...

A novel fuzzy reasoning method, called FSI (fuzzy similarity inference) is investigated in this paper. Firstly, the unified forms of FSI which the diverse implication operators can be employed are proposed. And the computational formulas for both fuzzy modus ponens (FMP) and fuzzy modus tollens (FMT) are obtained. Secondly, the unified forms of α-FSI method are established, and the formulas for...

The paper presents the design and implementation of a digital rule-relational fuzzy logic controller. Classical and decomposed logical structures of fuzzy systems are discussed. The second allows a decrease in the hardware cost of the fuzzy system and in the computing time of the final result (fuzzy or crisp), especially when referring to relational systems. The physical architecture consists o...

This paper presents an approach to similarity based approximate reasoning that elucidates the connection between similarity and existing approaches to inference in approximate reasoning methodology. A set of axioms is proposed to compute a reasonable measure of similarity between two fuzzy sets. Such a measure of similarity is then used at different stages to derive a conclusion in approximate ...

Hybridization of intelligent systems is a promising research field of modern computational intelligence concerned with the development of the next generation of intelligent systems. A fundamental stimulus to the investigations of hybrid intelligent systems is the awareness in the academic communities that combined approaches might be necessary if the remaining tough problems in artificial intel...

Fuzzy Logic, introduced by Zadeh along with his introduction of fuzzy sets, is a continuous multi-valued logic system. Hence, it is a generalization of the classical logic and the classical discrete multi-valued logic (e.g. Łukasiewicz’ three/many-valued logic). Throughout the years Zadeh and other researches have introduced extensions to the theory of fuzzy setts and fuzzy logic. Notable exten...

In this chapter, the capability of the fuzzy inference systems (FISs) to model and provide evaluations in the educational context is further explored through the merits of the intuitionistic fuzzy inference systems (IFISs). The Intuitionistic Fuzzy Logic enables the capture and expression of uncertainty and hesitancy with an IFIS model, thus it extends the fuzzy logic capabilities. In this chap...