A Self-Organizing Neural Fuzzy Inference Network

Como, Italy July 24-July 27

DOI Bookmark:

http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861428

IEEE-INNS-ENNS International Joint Co ...

	This Article
	PURCHASE ARTICLE: $19 PDF HTML IEEE Xplore Subscribers
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/Endnote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by G. Castellano Articles by A.M. Fanelli

	ASCII Text	x
	G. Castellano, A.M. Fanelli, "A Self-Organizing Neural Fuzzy Inference Network," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 5, pp. 5014, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5, 2000.

	BibTex	x
	@article{ 10.1109/IJCNN.2000.861428, author = {G. Castellano and A.M. Fanelli}, title = {A Self-Organizing Neural Fuzzy Inference Network}, journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on}, volume = {5}, year = {2000}, issn = {1098-7576}, pages = {5014}, doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861428}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on TI - A Self-Organizing Neural Fuzzy Inference Network SN - 1098-7576 SP EP A1 - G. Castellano, A1 - A.M. Fanelli, PY - 2000 VL - 5 JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on ER -

G. Castellano, Universit? degli Studi di Bari

A.M. Fanelli, Universit? degli Studi di Bari

A self-organizing neural network is proposed which is inherently a fuzzy inference system with the capability of learning fuzzy rules from data. The learning strategy consists of two phases: a self-organizing clustering to establish the structure of the network as well as the initial values of its parameters and a supervised learning phase for optimal adjustment of these parameters. After learning, the network encodes in its structure the essential design parameters of a fuzzy system. An example is given to illustrate the characteristics and capabilities of the proposed network.

Citation:

G. Castellano, A.M. Fanelli, "A Self-Organizing Neural Fuzzy Inference Network," ijcnn, vol. 5, pp.5014, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5, 2000

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.