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Fuzzy neural networks are found to be universal approximators when all the parameters of the network are adjusted simultaneously. Therefore, they have been used extensively classification and regression problems. Normally FNN uses TSK-type fuzzy rules where the consequent part of the rule base comprises linear terms. Thus FNNS may not be able to effectively handle chaotic time series like stock or...
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