By Bonissone P.P.
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Analysis. The deterioration with higher complexity is a manifestation of over tting. In this problem, a 4-rule ANFIS strikes a reasonably good balance. If so desired, a 9-rule ANFIS may be slightly better, but it shows some oscillations in the surface. The linguistic rulebase engineered from the data is easier to understand and modify than a pure neural network or a polynomial model, due to the use of fuzzy sets and fuzzy inference. We have also tried other approaches such as clustering using fuzzy spheres and ellipsoids to extract the rules.
Furthermore we would like to apply this reverse-engineering technique to other legacy-tables" which are currently used to represent unknown nonlinear relationships among process variables in tabular form. 9 High Throughput Requirements: Power Electronics Control Power electronics requires a mental shift of scale: actions that previously had taken seconds or milliseconds to compute and implement are now required in microseconds; actuator values may vary by two or more orders of magnitude from one end of the range of operation to the other.
13 Neural Networks Fuzzy logic enables us to translate and embed empirical, qualitative knowledge about the problem to be solved into reasoning systems capable of performing approximate pattern matching and interpolation. Fuzzy logic however does not have adaptation or learning features, since it lacks the mechanism to extract knowledge from existing data. Of course, it could be argued that it is possible to use fuzzy clustering methods, such as Fuzzy C-means Bezdek and Harris, 1978; Bezdek, 1981 to provide more accurate de nitions of the membership functions of the state and output variables, in a typical unsupervised mode.