Lecture20
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1. This lecture discusses genetic fuzzy systems and genetic algorithms for tuning different components of fuzzy rule-based systems, including rules, membership functions, and inference parameters. 2. Genetic algorithms can be used for genetic rule learning, genetic rule selection to determine the best rules, and genetic database learning to determine optimal membership function shapes. 3. Simultaneous genetic learning of multiple knowledge base components can improve results by accounting for dependencies between components, though it increases complexity.
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