The Open Cybernetics & Systemics Journal

2014, 8 : 829-834
Published online 2014 December 31. DOI: 10.2174/1874110X01408010829
Publisher ID: TOCSJ-8-829

A New ANFIS Model based on Multi-Input Hamacher T-norm and Subtract Clustering

Feng-Yi Zhang and Zhi-Gao Liao
Department of Management, Guangxi University of Science and Technology, Liuzhou, Guangxi, China 545000.

ABSTRACT

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 multi-input 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.

Keywords:

ANFIS, hamacher T-norm, subtract clustering, T-norm.