Research and application of data mining in enterprises consumption warning association

This paper proposes a structured item-sets time and space algorithm, which is used to find warning association rules between energy consumption monitoring points, according to the time characteristic and spatial characteristics of overall energy consumption in industrial enterprises, and the new algorithm can solve many difficulties that tradition mining algorithm encountered. The new algorithm has been improved on the basis of the classical Apriori algorithm. Introducing the time dimension and space dimension, new algorithm can dig more associated knowledge during different time periods and in different spatial layers. Through establishing minimum energy monitoring unit and adopting time-sharing and hierarchical data mining strategy, the new algorithm avoids producing excessive candidate sets. The improved algorithm has been applied in energy data analysis of production process of a large industrial enterprise in the domestic and achieved satisfying practical results.