Name
Title | ||
|---|---|---|
Extracting Rules From A (Fuzzy/Crisp) Recurrent Neural Network Using A Self-Organizing Map |
Abstract | ||
|---|---|---|
Although the extraction of symbolic knowledge from trained feedforward neural networks has been widely studied, research in recurrent neural networks (RNN) has been more neglected, even though it performs better in areas such as control, speech recognition, time series prediction, etc. Nowadays, a subject of particular interest is (crisp/fuzzy) grammatical inference, in which the application of these neural networks has proven to be suitable. In this paper, we present a method using a self-organizing map (SOM) for extracting knowledge from a recurrent neural network able to infer a (crisp/fuzzy) regular language. Identification of this language is done only from a (crisp/fuzzy) example set of the language. (C) 2000 John Wiley & Sons, Inc. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1002/(SICI)1098-111X(200007)15:7<595::AID-INT2>3.0.CO;2-5 | INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS |
Keywords | Field | DocType |
recurrent neural network | Neuro-fuzzy,Feedforward neural network,Fuzzy set operations,Computer science,Fuzzy logic,Recurrent neural network,Self-organizing map,Time delay neural network,Artificial intelligence,Adaptive neuro fuzzy inference system,Machine learning | Journal |
Volume | Issue | ISSN |
15 | 7 | 0884-8173 |
Citations | PageRank | References |
6 | 0.52 | 19 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Blanco | 1 | 141 | 11.03 |
| M. Delgado | 2 | 6 | 0.52 |
| M C Pegalajar | 3 | 154 | 12.01 |