关键词: 电费回收, 交费渠道, 黑洞熵, 模糊聚类

Abstract: How to efficiently recover consumers’ electric fees is a key task in power marketing. However, constructing appropriate payment channels may help different consumers fulfill their payments better. In this study, a novel method is proposed to categorize consumers’ payment preference based on black hole entropy fuzzy clustering and Bayesian model. The proposed method is very effective for massive user data, and can adaptively discovery the optimal preference clusters by means of maximum-a-posteriori reasoning and iterative sampling optimization. The experimental results obtained by using the proposed method on true sampled consumers’ payment records in Jiangsu province clearly demonstrate that, constructing more self-service payment channel is the most worthy, and the prepaid payment channel has most potential values.

Key words: electricity recovery, payment channel, black hole entropy, fuzzy clustering