【摘 要】
：
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
【机 构】
：
School of Mechanical Engineering
【基金项目】
：
国家自然科学基金;河北省自然科学基金
论文部分内容阅读
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 three-input and three-output signals was proposed with Legendre orthodoxy polynomial as basic pattern,based on fuzzy logic expert experiential knowledge and genetic-BP hybrid optimization algorithm.The model not only had definite physical meanings in its inner nodes,but also had strong self-adaptability,anti-interference ability,high recognition precision,and high velocity,thereby meeting the demand of high-precision flatness control for cold strip mill and providing a convenient,practical,and novel method for flatness pattern recognition.
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