Abstract
This paper presents a new hybrid diagnostic methodology. This new hybrid system involves statistical pre-processing, Artificial Neural Networks (ANN) and Fuzzy Logic (FL). The statistical pre-processing of data allows outliers to be eliminated (filtering) and dimensional reduction while keeping the most important data. Then, each process state is learned by one of the original constructive algorithms discussed: Multidimensional Fuzzy Sets (MFS) which fuzzyfies binary ANN or Generalized Radial Basis Functions (GRBF) learned by the Estimation Maximization (EM) algorithm. The final step is the final decision by Fuzzy Logic algorithms, in which an automatic defuzzification method is proposed. These methodologies produce some parameters which allows real-time to be performed.
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