Robust extraction of fuzzy rules with artificial neural network based on fuzzy inference system. (1st January 2012) - Czabanski, Robert; Jezewski, Michal; Jezewski, Janusz; Wrobel, Janusz; Horoba, Krzysztof
The paper presents a method of parameters estimation for artificial neural network based on fuzzy inference system (ANNBFIS). It is based on deterministic annealing, ε -insensitive learning by solving a system of linear inequalities and robust fuzzy c -means clustering. The proposed algorithm allows to improve the neuro-fuzzy modelling quality by increasing the generalisation ability and outliers robustness. To find the unknown number of fuzzy rules we proposed the procedure of robust clusters merging. The performance of the learning method is demonstrated through the benchmark sunspot prediction problem.