A hierarchical fuzzy rule-based learning system based on an information theoretic
نویسندگان
چکیده
This paper proposes a new novel method for the online construction of a Hierarchical Fuzzy Rule Based System (FRBS) to accurately model a function while retaining a level of human interpretability. The algorithm uses an information theoretic approach to limit the amount of uncertainty within each decision and to determine when a rule does not effectively model the underlying decision space. Experimental results are provided which compare the performance of the proposed system with existing approaches.
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تاریخ انتشار 2003