| Original language | English |
|---|---|
| Pages (from-to) | 211-243 |
| Journal | Fuzzy Sets and Systems |
| Volume | 150 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published (in print/issue) - 1 Mar 2005 |
Bibliographical note
Other Details------------------------------------
Fuzzy modeling of complex systems requires the extraction of a suitable collection of fuzzy rules from the available data set. This is often a difficult challenge. While neural networks have the ability to learn the fuzzy rules automatically, it is usually not possible to extract the rules from the trained neural network. The importance of this paper is that it presents a new self-organising fuzzy neural network that is able to extract fuzzy rules from the data set, and implement structure and parameter learning, with a high accuracy. The automatic addition and pruning techniques implemented ensure a compact network.