The Newly AND-OR FNN Modeling and Application

Abstract:

The novel multilayer feed-forward AND-OR fuzzy neural network (AND-OR FNN) is proposed in this paper. The main feature is shown not only in reducing the input space by special inner structure of neurons, but also auto-extracting the rules by the structure self-organization and parameter self-learning. The equivalent is proved that the network structure and fuzzy inference. The whole structure of network is optimized by genetic algorithm to extract if-then rules. This designing approach is employed to modeling an AND-OR FNN controller for ship control. Simulated results demonstrate that the number of rule base is decreased remarkably and the performance is much better than ordinary fuzzy control, illustrate the approach is practicable, simple and effective.

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 846-852
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.846
• Online since: January 2012
• Authors: Jiang Hua Sui, Qiang Ma
• Keywords: AND-OR FNN, In-Degree, Relevant Degree, Ship Control

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