On-line learning, reasoning, rule extraction and aggregation in locally optimized evolving fuzzy neural networks

摘要

Fuzzy neural networks are connectionist systems that facilitate learning from data, reasoning over fuzzy rules, rule insertion, rule extraction, and rule adaptation. The concept of a particular class of fuzzy neural networks, called FuNNs, is further developed in this paper to a new concept of evolving neuro-fuzzy systems (EfuNNs), with respective algorithms for learning, aggregation, rule insertion, rule extraction.