多维时序模糊关联规则在高炉炉温预报中的应用

基金项目:

国家经济贸易委员会资助项目(No.02BK-101-8)

详细信息

Application of multidimensional time series fuzzy association rules for hot metal temperature forecasting in a blast furnace

1. School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China;
2. School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China;
3. Wuhan Iron and Steel Group Corporation, Wuhan 430083, China

摘要: 根据目前高炉炉温预报推理规则都是由高炉专家根据经验制定的情况,提出了一种新的规则生成方法——数据挖掘获取高炉炉温预报关联规则.针对现有挖掘算法的不足,提出了一种改进的多维时间序列模糊关联规则挖掘算法,该算法基于时间子序列和子序列间隔的双重模糊化,避免了挖掘结果"时间边界锐化"的问题.该算法应用于武钢的1^#高炉,挖掘效果良好.
- 高炉 /
- 专家系统 /
- 炉温预报 /
- 模糊关联规则 /
- 时间序列
Abstract: Confronted by the present state that the rules for hot metal temperature forecasting are made merely on the base of the experience of blast furnace (BF) experts, a new approach to the rules established through association rules mining from BF data was put forward. The algorithm of multidimensional time series rules mining was improved. The improved algorithm, which bases on the fuzziness of both subsequence and suhsequence interval, avoids the influence of "time border sharpness" on the result of mining. The algorithm was applied to No. 1 BF at Wuhan Iron and Steel Group Corporation, and its effects turned out to be satisfactory.
- blast furnace（BF） /
- expert system /
- hot metal temperature forecast /
- fuzzy association rules /
- time series