A fuzzy-rule-fusion based fuzzy modeling method and its application
Zhe Xu, Zhizhong Mao · Kongzhi yu juece · 2013
To effectively use the empirical knowledge to compensate for incomplete training data coverage,a fuzzy modeling method that incorporates empirical knowledge in the form of TSK(Takagi-Sugeno-Kang) fuzzy rules is proposed.In the structure identification process,a fuzzy rule fusion method is proposed to determine the initial fuzzy rules.In the parameter identification process,the original objective function of the gradient descent method is improved and the evaluating parameter of the accuracy of empirical knowledge is introduced to trade off the influence of sample data and empirical knowledge.The numerical simulation and engineering case studies show that the proposed method can offer more reliable and accurate forecasting values.