Anzeige
Erschienen in:
1998 | OriginalPaper | Buchkapitel
A Learning Method of Fuzzy Inference Rules Using Vector Quantization
verfasst von : Kazuya Kishida, Hiromi Miyajima
Erschienen in: ICANN 98
Verlag: Springer London
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Some models using self-organization systems of neural networks are proposed in recent studies. These models show good results in point of the number of fuzzy rules in high dimensional problems. However, most of these models determine a distribution of initial fuzzy rules by considering only input data. In this paper, we propose a method considering not only input data but also output data. In order to demonstrate the validity of the proposed method, some numerical examples are performed.