Abstract
The simplified fuzzy reasoning model having multi-layer structure has a feature that generation of fuzzy rules is easy even under actual conditions. However, it is reported that redundant fuzzy rules are generated as division layers are iteratively increased. In this paper, we propose a fuzzy reasoning model of multiple division layers, which has a weight in the reasoning output. We reduce redundant fuzzy rules by tuning up the weight using an evaluation function based on Minkowski norm. Moreover, the validity of the proposed method is verified by identification experiments of two nonlinear functions having sparse domains in teaching data. Finally, we apply the proposed method to a modeling of ceramic kiln, and confirm that it is also effective for actual problems.
