Levenberg-Marquardt method for ANFIS learning
Jyh‐Shing Roger Jang, Eiji Mizutani · 2002
Presents the results of applying the Levenberg-Marquardt method (K. Levenberg, 1944, and D.W. Marquardt, 1963), which is a popular nonlinear least-squares method, to the ANFIS (Adaptive Neuro-Fuzzy Inference System) architecture proposed by Jang (IEEE Trans. on Systems, Man and Cybernctics, vol. 23, no. 3, pp 665-685, May 1993). Through empirical studies, we discuss the strengths and weaknesses of using such an efficient nonlinear regression technique for neuro-fuzzy modeling, and explain the tradeoffs between mapping precision and membership function interpretability.