A New ANFIS Model based on Multi-Input Hamacher T-norm and Subtract Clustering
Feng-Yi Zhang, Zhigao Liao · The Open Mechanical Engineering Journal · 2014
This paper proposed a novel adaptive neuro-fuzzy inference system (ANFIS), which combines subtract clustering, employs adaptive Hamacher T-norm and improves the prediction ability of ANFIS. The expression of multiinput Hamacher T-norm and its relative feather has been originally given, which supports the operation of the proposed system. Empirical study has testified that the proposed model overweighs early work in the aspect of benchmark Box- Jenkins dataset and may provide a practical way to measure the importance of each rule.