Rules Mining and Fuzzy Inferring for Temperature Forecasting of Hot Metal in BF Production
Focusing on the limitations of current methods that inference rules are acquired mostly according to the experts’ experience, a new rules generation method is proposed for the temperature forecasting of hot metal in BF production. According to this method, the fuzzy association rules are worked out by data mining technology. Furthermore, the key algo- rithm of the fuzzy inference system is put forward considering the specification of the fuzzy association rules mined out.
blast furnace temperature forecast data mining fuzzy inferring
GUO Hong-wei ZHANG jian-liang LIU Zheng-jian YANG Tian-jun
School of Metallurgical and Ecological Engineering USTB, Beijing 100083, China
国际会议
The 5th International Congress on the Science and Technology of Ironmaking(第五届国际炼铁科技大会 ICSTI09)
上海
英文
974-978
2009-10-20（万方平台首次上网日期，不代表论文的发表时间）