Power supply reliability is an important indicator of power supply service level. A power supply reliability model based on correlation analysis and deep belief network is proposed.Firstly

Pearson coefficient is used to select the outage times

maximum load and average price coefficient of consumer electricity as the input feature set. Then the feature set is put into the established deep belief network

the parameters of the model are optimized by layer- by-layer unsupervised training method and back propagation training method. The model is used to predict the power supply reliability. Finally

the proposed framework is compared with artificial neural network

support vector regression and autoregressive integrated moving average. Simulation results show the effectiveness of the proposed power supply reliability forecasting model.