Abstract: General Regression Neuro-Fuzzy? Network, which combines the properties of conventional General Regression Neural Network and Adaptive Network-based Fuzzy Inference System is proposed in this work. This network relates to so-called “memory-based networks”, which is adjusted by one-pass learning algorithm.

Keywords: memory-based networks, one-pass learning, Fuzzy Inference Systems, fuzzy-basis membership functions, neurons at data points, nonlinear identification.

ACM Classification Keywords: F.1 Computation by abstract devices - Self-modifying machines (e.g., neural networks), I.2.6 Learning - Connectionism and neural nets, G.1.2. Approximation – Nonlinear approximation.

Link:

GENERAL REGRESSION NEURO–FUZZY NETWORK FOR IDENTIFICATION OF NONSTATIONARY PLANTS

Yevgeniy Bodyanskiy, Nataliya Teslenko

http://www.foibg.com/ijitk/ijitk-vol02/ijitk02-2-p05.pdf