Prediction of Electricity Tariff Recovery Risk based on Hybrid Feature Selection Algorithm

In order to fully extract the information that affects the user's arrears and reduce the dimension of features, a hybrid feature selection algorithm based on the particle swarm optimization algorithm with contraction factor (PSOCF) and whale optimization algorithm (WOA), namely, PSOCFWOA is proposed. The PSOCFWOA algorithm combines the advantages of the two algorithms that PSOCF and WOA. The experimental results show that the proposed PSOCFWOA can effectively reduce a large number of redundant or irrelevant features and stably improve the prediction results in the case of low execution time, compared with two state-of-the-art optimization algorithm, and six well-known feature selection approaches to the risk prediction of electricity tariff recovery for power customers.