Model of Multi-stage Neural Fuzzy System with Hybrid Learning Algorithm
Lan Huang · Journal of Jilin University(Science Edition) · 2008
A multi-stage Neural Fuzzy System(NFS) model based on syllogistic fuzzy reasoning is proposed in this paper.From the stipulated input-output data pairs, an appropriate syllogistic fuzzy rule set can be generated via structure learning(using Genetic Algorithm) and parameter learning(using Back-propagation Neural Network) procedures proposed in this paper.In addition,by means of solving Benchmark problem and unmanned vehicl control problem,we discussed and analyzed the performance of the proposed model in terms of effectiveness and robustness as compared with single-stage NFS models.