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《Journal of University of Science and Technology Beijing》 2006-09
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Expert system for controlling sinter chemistry based on neural network prediction

LONG Hongming~ 1) , FAN Xiaohui~ 1) , CHEN Xuling~ 1) , JIANG Tao~ 1) , SHI Jun~ 2) , SONG Qingyong~ 2) , YANG Xiaodong~ 2) 1) School of Resources Processing and Bioengineering, Central South University, Changsha 410083, China2) Steelmaking Factory, Panzhihua New Steel & Vanadium Co. Ltd., Panzhihua 617022, China  
A sintering predictive model of chemical composition based on many periods was developed by the BP neural network algorithm with appending momentum and adaptive variable step size linear reinforcement. Using knowledge base that was based on database technology and illation with forward inference, an expert system was designed for controlling sinter chemistry. Since the system was plunged into application, the hit ratio of the predictive model is over 90% steadily, and the acceptance of operation suggestion is 92%. The goal of controlling chemical composition steadily is actualized.
【Fund】: 国家自然科学基金;; 上海宝钢集团公司联合资助项目(No.50374080);; 中南大学研究生教育创新工程基金资助项目(No.042310011)
【CateGory Index】: TP182
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