Different Approaches to Induce Cooperation in Fuzzy Linguistic Models Under the COR Methodology
Nowadays, Linguistic Modeling is considered to be one of the most important areas of application for Fuzzy Logic. It is accomplished by linguistic Fuzzy Rule-Based Systems, whose most interesting feature is the interpolative reasoning developed. This characteristic plays a key role in their high performance and is a consequence of the cooperation among the involved fuzzy rules.
A new approach that makes good use of this aspect inducing cooperation among rules is introduced in this chapter: the Cooperative Rules methodology. One of its interesting advantages is its flexibility allowing it to be used with different combinatorial search techniques. Thus, four specific metaheuristics are considered: simulated annealing, tabu search, genetic algorithms and ant colony optimization. Their good performance is shown when solving a real-world problem.
KeywordsMean Square Error Tabu Search Fuzzy Rule Heuristic Information Linguistic Rule
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