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.
|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||International Joint Conference on Neural Networks (IJCNN'2000)|
|Period||24/07/00 → 27/07/00|