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This paper presents a new method of using hybrid intelligent systems to solve the problem of tuning the parameters of a fuzzy logic controller. Two different hybrid intelligent systems are introduced in this paper. Each system proposes learning in a two-stage iterative process. The first system combines a fuzzy logic controller with genetic algorithms to form the iterative genetic based fuzzy logic...
Wireless sensor/actuator networks (WSANs) are rapidly increasing due to the recent advances in radio frequency, computing and sensing technologies. In particular, quality of service (QoS) technologies management remains an important issue yet to be investigated. In this paper, a fuzzy-genetic approach based QoS management (FG-QM) scheme is developed for WSANs with constrained resources and in dynamic...
This paper tries to apply a genetic algorithm-based method to fuzzy rule-base system for fuzzy classification with minimum fuzzy rules, which simultaneously enhances or maintain the performance of the fuzzy classification system with fuzzy rule-base. That is, the optimization is included with the minimization of the number of the extracted fuzzy rules and the maximization of the performance of the...
This paper proposes an approach for inverse problem solving based on the description of the interconnection between unobserved and observed parameters of an object (causes and effects) with the help of fuzzy IF-THEN rules. The essence of the approach proposed consists in formulating and solving the optimization problems, which, on the one hand, find the roots of fuzzy logical equations, corresponding...
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