A New Multimodel Approach for Complex Processes Modeling Based on Classification Algorithms: Experimental Validation

In this paper, a new multimodel approach for complex systems modeling based on classification algorithms is presented. It requires firstly the determination of the model-base. For this, the number of models is selected via a neural network and a rival penalized competitive learning (RPCL), and the operating clusters are identified by using the fuzzy K-means algorithm. The obtained results are then exploited for the parametric identification of the models. The second step consists in validating the proposed model-base by using the adequate method of validity computation. An experimental validation is presented in this paper which shows the efficiency of the proposed approach.