A genetic approach to fuzzy learning

Abstract

The approach proposed allows supervised approximation of multi-input/multi-output (MIMO) systems. Typically a small number of fuzzy rules are produced. The learning capacity is considerable, as is shown by the numerous applications developed. The paper gives a significant example of how the fuzzy models developed are generally better than those to be found in recent literature concerning both the approximation capability and simplicity.