For the problems occurring in a least square method model, a fuzzy model, and a neural network model for flatness pattern recognition, a fuzzy neural network model for flatness pattern recognition with only threeinput and threeoutput signals was proposed with Legendre orthodoxy polynomial as basic pattern, based on fuzzy logic expert experiential knowledge and geneticBP hybrid optimization algorithm. The model not only had definite physical meanings in its inner nodes, but also had strong selfadaptability, antiinterference ability, high recognition precision, and high velocity, thereby meeting the demand of highprecision flatness control for cold strip mill and providing a convenient, practical, and novel method for flatness pattern recognition.
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