We introduce a hybrid architecture that dwells on the ideas of fuzzy rule-based computing and an approximation scheme (SOPNN). The hybrid system is combined to get a novel heuristic approximation method. This composite structure overcomes the shortcomings of the individual methods especially it solves drawbacks of SOPNN while maintaining their desirable features. The combined method is efficient and much more accurate than either of the two individual schemes as well as other modeling methods. A three-input nonlinear static function is demonstrated for the utility of the proposed approach.
['Dongwon Kim', 'Jang-Hyun Park', 'Gwi-Tae Park']
Combination of fuzzy rule based model and self-organizing approximator technique: a new approach to nonlinear system modeling