Getting Complete Rulebase from Recorded Data

Abstract: In this paper, an approach is introduced to get complete rulebase fiom recorded data. At the beginning, a small number of fuzzy sets are defined on each variable to get a complete rulebase. In this case, even if there are missing rules, the rulebase can be completed by knowledge easily. Then, the number of fuzzy sets increased step by step until the performance of the model reach a certain level or cannot be improved further. During this procedure, if the generated rulebase is incomplete, the model constructed at last step can be used to complete the rulebase at this step. Finally, the proposed method is used to build the model of a reheating furnace and the simulation results show the effectiveness of the proposed method