By Topic

The diagnostic reasoning based on fuzzy self-organizing neural network and its application

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Yan-ling Han ; CIMS & Robot Center, Shanghai Univ., China ; Yun Chen ; Shou-qi Cao ; Zhi-xiong Ying
more authors

By means of the maturational fuzzy theory and the self-organizing map (SOM) neural network which is prepotent in the way of information mapping and self-organizing characteristics, this paper combines the fuzzy theory with SOM neural network having the feature of pinpoint nonlinearity, and applies it to the field of fault diagnosis for large-scale electro-mechanical equipments. The network structure and theory of learning of SOM are exhausted in detail, and the diagnostic principle and the implementation strategy of fault reasoning based on fuzzy self-organizing map (FSOM) neural network are researched. Finally, we verify the correctness and the practicability of this method by the instance during the procedure of diagnostic reasoning.

Published in:

Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on  (Volume:4 )

Date of Conference:

26-29 Aug. 2004