数据信息挖掘在热工控制过程中的应用

Application of Data Mining in Thermal Control Process

近年来数据信息挖掘技术随机器学习研究兴起,其可从大量无序的数据中找出潜在规律或趋势,生成对应的知识规则来指导决策。将数据信息挖掘技术与电厂热工控制相结合,针对火电厂运行数据的特点,应用K-means聚类分析与FP-growth关联规则相结合的算法,提出了指导电厂运行优化的新方法,实验表明该算法有较高的性能。

In recent years, data mining technology has been rising with the study of machine learning. It can discover the potential pattern and trend from a large amount of disordered data, and generate the corresponding knowledge rules for the decision making. In this paper, data mining technology is combined with the thermal control of the power plant. According to the characteristics of the operation data from the thermal power plant, this paper combines K- means clustering analysis and FP-growth association rules algorithm, and introduces a new method to improve the power plant operation optimization. Experiments show that the algorithm has high performance.