Interval Water Demand Forecasting Model in Deep Confidence Network based on Wavelet Model ｏｒ BP Neural Network

Qiang Wang

Human Resources Office, Shandong Vocational College of Industry, Zibo, 256414, China

Abstract: The traditional deep belief network interval water demand predictive model can achieve the pur-pose of predicting water demand, but the predictive model still has certain instability in water demand fore-casting, so a deep belief network interval water demand predictive model based on wavelet model ｏｒ BP neural network is proposed. Around the construction of a deep belief network interval water demand predic-tive model, firstly, we use the wavelet model to detect the depth of groundwater level and then perform the next step of reducing the water demand, and use the BP neural network to calculate the water demand to build the water demand predictive model. The experimental results show that deep belief network interval water demand predictive model based on wavelet model ｏｒ BP neural network can improve the accuracy of certain water demand.

Keywords: Wavelet model; BP neural network; Water demand; Prediction