Power Big Data Apriori Parallel Algorithm Based on Posterior Double Threshold

摘要

Aiming at the problem of low computational efficiency of traditional power data, this paper proposes a posteriori double-threshold power big data Apriori parallel computing method based on Boolean matrix. The Boolean matrix is used to compress and store data, and the removal rate is introduced to pruning the data. The double-threshold parallel computing method is used, and then the lifting degree is used to verify it. The Boolean matrix-based posterior dual-threshold power big data Apriori parallel computing method is used to solve the problem of low efficiency of traditional power big data calculation. The experimental results show that the improved algorithm can effectively improve the computational power and computational efficiency of power big data.