FUGENESYS - A FUZZY GENETIC NEURAL SYSTEM FOR FUZZY MODELING

The author has developed a novel approach to fuzzy modeling from input -output data, Using the basic techniques of soft computing, the method allows supervised approximation of multi-input multi-output (MIMO) sy stems. Typically, a small number of rules are produced, The learning c apacity of FuGe-NeSys is considerable, as is shown by the numerous app lications developed. The paper gives a significant example of how the fuzzy models developed are generally better than those to be found in literature as concerns simplicity and both approximation and classific ation capabilities.