Title

Granularity and Specificity in Fuzzy Rule-Based Systems

Document Type

Book Chapter

Publication Date

2001

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Abstract

The structure of fuzzy models produced by a heursitic analysis of the problem domain is compared with that of models algorithmically generated from training data. The trade-offs between granularity, specificity, interpretability, and efficiency are examined for rule-bases produced in each of these manners. An algorithm that combines rule learning with region merging is introduced to incorporate beneficial features of both the heuristic and learning approaches to producing fuzzy models.

DOI

10.1007/978-3-7908-1823-9_11