An AND-OR Fuzzy Neural Network and Ship Application

摘要：

A novel multilayer feed-forward AND-OR fuzzy neural network (AND-OR FNN) and a piecewise optimization approach are proposed in this paper. The equivalent is proved between the architecture of AND-OR FNN and fuzzy weighted Mamdani inference. The main superiority is shown in not only reducing the input space by special inner structure of neurons, but also auto-extracting the rule base by the structure optimization of network. The optimization procedure consists of two phases, first the blueprint of network is reduced by GA (Genetic Algorithm) and PA (Pruning Algorithm); the second phase, the parameters are refined by ACO (Ant Colony Optimization). The AND-OR FNN ship controller system is designed based on input-output data to validate this method. Simulated results demonstrate that the number of rule base is decreased remarkably, the performance is much better than ordinary fuzzy control and the approach is practicable, simple and effective.

作者: Jianghua Sui Guang Ren

作者单位: Marine Engineering College Dalian Maritime University Dalian, Liaoning Province, 116026, China

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 605-610

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）