Fuzzy logic is a logical calculus which operates with many truth values (while classical logic works with the two values of true and false). Since fuzzy logic considers the truth of scientific statements like something softened, it is fruitfully applied to the study of biological phenomena, biology is indeed considered the field of complexity, uncertainty and vagueness. In this paper fuzzy logi...

Classically, most programming languages use in a predefined way the notion of “string” as an standard data structure for a comfortable management of arbitrary sequences of characters. However, in this paper we assign a different role to this concept: here we are concerned with fuzzy logic programming, a somehow recent paradigm trying to introduce fuzzy logic into logic programming. In this sett...

controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. interval type-2 fuzzy logic systems (it2fls) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. in contrast, adaptive sliding modecontrol (asmc) provides...

Fuzzy logic is a mathematical approach towards the human way of thinking and learning. Based on if-then rules, we can design fuzzy controllers with the intuitive experience of human beings. However, it is not practical for a designer to find necessary number of rules and determine appropriate parameters by hand. Hence, we incorporate a reinforcement learning method with basic fuzzy rules so tha...

Interval type-2 fuzzy logic systems have a wide range of applications due to their abilities to handle uncertainties compared to their type-1 counterparts. This paper presents an approach for developing closed-form mathematical representations for interval type-2 fuzzy logic systems. Having such a representation can be useful in real-time implementation of the system and in its mathematical ana...

The paper discusses a mathematical nature of signs and symbols, and relates it to information processing and understanding, structure of the mind and brain, learning, and pattern recognition. I discuss past limitations of algorithms and neural networks, combina-torial complexity, the roles of concepts and emotions in mind’s mechanisms, and various types of logic underlying mathematical techniqu...

New trends and the effect of key factors influence the quality of the holes produced by ECM processes. Researchers developed a fuzzy logic controller by adding intelligence to the ECM process. Maintaining optimum ECM process conditions ensures higher machining efficiency and performance. This paper presents the development of a fuzzy logic controller to add intelligence to the ECM process. An e...

we study the history and recent developments in nonelementarymodel theory focusing on the framework of abstractelementary classes. we discuss the role of syntax and semanticsand the motivation to generalize first order model theory to nonelementaryframeworks and illuminate the study with concrete examplesof classes of models. this second part continues to study the question of catecoricitytrans...

Fuzzy logic is an organized and mathematical method of handling inherently imprecise concepts through the use of membership functions, which allows membership with a certain degree. It has found application in numerous problem domains. It has been used in the interval [0, 1] fuzzy clustering, in pattern recognition and in other domains. In this paper, we introduce fuzzy logic, fuzzy clustering ...

Direct-sequence Code-division multiple-access (DS-CDMA) has emerged as proper format for communication systems. As a result of multiple-access interference (MAI), inter-symbol interference (ISI), narrowband interference (NBI) and nonlinearities in channels, DS-CDMA systems can suffer deterioration in performance . New techniques to suppress narrow-band and multiple-access interference for sprea...