Mining fault association rules in the perception layer of electric power sensor network based on improved Eclat

Aiming at the problem that existing association rule mining algorithms cannot quickly mine faulty association rules in the current perception layer of electric power sensor networks, an improved eclat mining algorithm fast_eclat is proposed. The algorithm combines the characteristics of sparse data and large number of transactions at the perception layer of the power sensor network, and adopts a set intersection strategy based on pruning cross-counting, which reduces the computational complexity and improves the computational efficiency of the algorithm, which can more effectively deal with fault association rules. Comparative analysis through simulation experiments shows that the fast_eclat algorithm has better performance in the face of sparse data and large number of transactions.