Training Algorithm of Fuzzy Neural Network Based on Improved T-S Fuzzy Reasoning
Sonil Gwak · 2011
A training algorithm of fuzzy neural network based on improved T-S fuzzy reasoning was proposed in the predicate model design,in order to reduce the complexities of the algorithm.The main work is as below.Firstly,improved T-S fuzzy reasoning method based on moving rate is defined.Then,compared with existing fuzzy reasoning method based on composed rules and distance-type fuzzy reasoning method,new fuzzy reasoning algorithm has a less amount of complexity in calculating and is more effective.Finally,the training algorithm of fuzzy neural network is improved,and it can be applied in weather forecast and security situation prediction.Test results show that this method significantly improves the effectiveness of training,reduces the order of training,time complexity and training error.