Autonomous Mountain-Clustering Method Applied to Fuzzy Systems Modeling
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چکیده
The main problem in constructing fuzzy systems consists on finding an initial structure for it. The structure of fuzzy systems is composed of the number of fuzzy sets partitioning each variable and their distribution in the universe of discourse. This paper proposes the use of the autonomous-mountain clustering method to identify this structure for applications in fuzzy systems modeling. To investigate the potentialities of the proposed approach, a fuzzy model of an experimental electrohydraulic system is constructed with its structure identified by the autonomous clustering algorithm. Although neural networks are supposed to cover any function with arbitrary low error given enough time and neural elements, in the present case, neural net architecture 3-6-1 could only have similar results to the autonomously initialized fuzzy model if we used adjustable learning rate back propagation.
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