Abstract
This paper presents a neuro-fuzzy system by using the Kohonen's self-organizing feature map algorithm, not only for its vector quantitization feature, but also for its topological property. This property prevents the proposed neuro-fuzzy system from suffering from a drawback like any of the conventional clustering-algorithm-based fuzzy systems, i.e. the optimal number of clusters or some kind of similarity threshold must be predetermined. Associated with the self-organizing feature-map-based fuzzy system is a hybrid learning algorithm, which is for initial parameters setting and fine-tuning the parameters of the system.
| Original language | English |
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| Pages | 20-25 |
| Number of pages | 6 |
| State | Published - 2000 |
| Event | International Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy Duration: 24 Jul 2000 → 27 Jul 2000 |
Conference
| Conference | International Joint Conference on Neural Networks (IJCNN'2000) |
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| City | Como, Italy |
| Period | 24/07/00 → 27/07/00 |