A Rough T-S Fuzzy Model

A rough T-S fuzzy model that uses rough set to design the structure of T-S fuzzy model is proposed. Fuzzy c-means clustering is used to transform the continuous attributes to the discretized ones and partition the input space. Heuristic attribute reduction algorithm based on attribute significance deals with the discretized decision table to remove redundant condition attributes. Concise decision rules are extracted according to the threshold of degree of support, confidence and coverage. The rules of T-S fuzzy model are got according to the extracted decision rules. Antecedent parameters of T-S fuzzy model are determined according to fuzzy partition result, and consequent parameters are identified by least square method. Fuzzy rules of the proposed model have clear physical meaning and simplified structure. Moreover, a study algorithm is no longer needed to optimize the parameters of fuzzy model. Finally, the validity of the proposed model is verified by water treatment modeling experiment.