National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61573299]; Science and Technology Plan Project of Hunan Province [2016TP1020]; Natural Science Foundation of Hunan ProvinceNatural Science Foundation of Hunan Province [2017JJ2011, 2017JJ3315]; Research Project of the Education Department of Hunan Province [17A031]
机构署名：
本校为通讯机构
院系归属：
物理与电子工程学院
摘要：
Effective and accurate water demand prediction is an important part of the optimal scheduling of a city water supply system. A novel deep architecture model called the continuous deep belief echo state network (CDBESN) is proposed in this study for the prediction of hourly urban water demand. The CDBESN model uses a continuous deep belief network (CDBN) as the feature extraction algorithm and an echo state network (ESN) as the regression algorithm. The new architecture can model actual water demand data with fast convergence and global optimiza...
