Research on the Improvement of Association Rule Algorithm for Power Monitoring Data Mining
Mengmeng Cao, Chaoyou Guo · 2017
Power monitoring device collects large amounts of data which is only used for alarm. These data contains a wealth of knowledge (rules), but has not been effectively excavated. Therefore, based on the upper triangular matrix (UTM), an improved association rule algorithm is introduced in this paper. The algorithm can streamline the size of candidate sets and minimize the number of traversing and scanning for the database. So, the efficiency of rule acquisition is significantly improved. The feasibility and validity of the improved algorithm are verified by an experiment which is conducted in a power monitoring data through association rule analysis. It provides an effective approach for excavating power monitoring data and discovering of association rules.