基于KDD和案例推理的热轧负荷分配法  

Application of Case-based Reasoning Technique with KDD in Load Distribution of Hot Strip Mill

作　　者：丁敬国[1] 胡贤磊[1] 焦景民[1] 佘广夫[1] 刘相华[1] 

机构地区：[1]东北大学轧制技术及连轧自动化国家重点实验室,辽宁沈阳110004

出　　处：《轧钢》2007年第1期53-55,共3页Steel Rolling

基　　金：国家自然科学基金资助项目(50104004)

摘　　要：采用案例推理技术建立轧制规程案例库,并通过KDD挖掘技术从轧制运行数据库发现案例修改规则以适应不同轧制条件和不同轧制规格,由此建立一种基于经验和知识模型的热轧负荷分配法。试验表明,该方法提高了问题求解效率和质量,且更符合实际生产特点。A case-based reasoning technique is used to set up a database of load distribution and to discover modified regulation from rolling database by KDD mining technique, which suits for different rolling condition and specification, therefore, to set up a load distribution for hot strip mill based on experience and knowledge model. This method improves the efficiency and quality of trouble shooting, and it is up to the characteristic in practical producing much more, which provides a new applied theory and technique for hot strip producing.

关 键 词：热连轧 负荷分配 案例推理 知识发现 

分 类 号：TG335.55[金属学及工艺—金属压力加工]