Fuzzy Neural Model for Flatness Pattern Recognition |
| |
Authors: | JIA Chun-yu SHAN Xiu-ying LIU Hong-min NIU Zhao-ping |
| |
Affiliation: | School of Mechanical Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China |
| |
Abstract: | 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. |
| |
Keywords: | flatness pattern recognition Legendre orthodoxy polynomial genetie-BP algorithm fuzzy neural network |
本文献已被 维普 万方数据 ScienceDirect 等数据库收录! |
| 点击此处可从《钢铁研究学报(英文版)》浏览原始摘要信息 |
|
点击此处可从《钢铁研究学报(英文版)》下载全文 |
|