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In this paper, an integration of fuzzy logic controller (FLC) and genetic algorithm (GA) is developed with a view to make the design process fully automatic, without requiring any human expert knowledge. Here, GA is used in two stages simultaneously: the first stage involves selection and definition of fuzzy rules, while the second stage performs an optimal selection of membership function types associated...
Fuzzy controllers are represented by if-then rules and thus can provide a user friendly and understandable knowledge representation. Evolutionary algorithms have been widely used for optimal design of fuzzy logic controllers (FLCs). In this paper, we present an evolutionary algorithm based on Tabu Search (TS) for generating knowledge bases for fuzzy logic systems. The algorithm dynamically adjusts...
In this paper, an immune inspired multi-objective fuzzy modeling (IMOFM) mechanism is proposed specifically for high-dimensional regression problems. For such problems, high predictive accuracy is often the paramount requirement. With such a requirement in mind, however, one should also put considerable efforts in making the elicited model as interpretable as possible, which leads to a difficult optimization...
Tuning membership functions parameters of fuzzy logic controllers (FLC) has proven to be an effective method in improving the performance of this type of controllers. However, simulations usually require a considerable amount of time to optimize the membership functions parameters. In this paper a new methodology is proposed to optimize the performance of the FLC. The FLC in this paper is simply designed...
Integration and adaptation of artificial intelligent designs with fuzzy inference techniques is an active area of research that can be used to meet the challenges of regeneration processes. Urban regeneration activities in built environment are complex and require a close collaboration between designers and planners in order to achieve a design plan that is environmentally robust and sustainable....
Learning fuzzy rule-based systems with genetic algorithms can lead to very useful descriptions of several optimization and search problems. In the fuzzy logic method, when the inputs to the fuzzy controller in any process are increased, then the number of rules increases exponentially. To overcome the above problem, genetic algorithm (GA) is used. Genetic algorithm is a search and optimization technique...
In order to realization electronic parts product appearance quality detection control, one kind of processor based on the intelligent knowledge automatic extraction and system intelligence modeling was presented. In the processor, wavelet-fuzzy technique and neural network technique are combined. Uses the fuzzy wavelet extraction image feature, and wavelet function is used as fuzzy membership function...
The search for the ultimate architecture for cross-layer optimization in cognitive radio networks is characterized by challenges such as modularity, interpretability, imprecision, scalability, and complexity constraints. In this article we propose fuzzy logic as an effective means of meeting these challenges, as far as both knowledge representation and control implementation are concerned.
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