Title :
Unbiased use of data for input selection in fuzzy modelling
Author :
Jang, Jyh-Shing Roger
Author_Institution :
Dept. of Comput. Sci., Tsinghua Univ., Hsinchu, Taiwan
Abstract :
This paper describes an efficient method that computes the leave-one-out error for a linear model. The proposed method is able to find an unbiased performance index of a modeling approach involving the use of the least-squares method. The obtained performance index can then be used for model structure determination. A simple example of polynomial fitting is used to show the feasibility of the method. An advanced example of dynamical system identification via adaptive neuro-fuzzy inference system modeling is used to demonstrate the proposed method in practice for input selection in neuro-fuzzy modeling
Keywords :
adaptive systems; computational complexity; fuzzy systems; identification; least squares approximations; minimisation; modelling; neural nets; performance index; adaptive neurofuzzy inference systems; computational complexity; fuzzy modelling; identification; input selection; least-squares estimation; leave-one-out error; model structure; neurofuzzy modeling; performance index; polynomial fitting; Adaptive systems; Computational complexity; Councils; Design methodology; Equations; Error analysis; Multi-layer neural network; Polynomials; Testing; Vectors;
Conference_Titel :
Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4863-X
DOI :
10.1109/FUZZY.1998.687561