Investigation of automatic rule generation for hierarchical fuzzy systems
R. Holve · 2002
The paper is based upon a method for the automatic generation of rules for hierarchical fuzzy associative memories (HIFAM). The effectiveness and termination of a general description of a training algorithm for HIFAMs is proved and experimental results on how HIFAMs evolve during training are given as well as a comparison with other machine learning techniques.