2023, Volume 17, Issue 2
Frontiers of Environmental Science & Engineering >> 2023, Volume 17, Issue 2 doi: 10.1007/s11783-023-1622-3
A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting
1. College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China;2. Smart Water Joint Innovation RD Center, Tongji University, Shanghai 200092, China;1. College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China;2. Smart Water Joint Innovation RD Center, Tongji University, Shanghai 200092, China;1. College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China;2. Smart Water Joint Innovation RD Center, Tongji University, Shanghai 200092, China;1. College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China;2. Smart Water Joint Innovation RD Center, Tongji University, Shanghai 200092, China;1. College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China;2. Smart Water Joint Innovation RD Center, Tongji University, Shanghai 200092, China;1. College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China;2. Smart Water Joint Innovation RD Center, Tongji University, Shanghai 200092, China;1. College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China;2. Smart Water Joint Innovation RD Center, Tongji University, Shanghai 200092, China
Next Previous
Abstract
● A novel deep learning framework for short-term water demand forecasting.
京公网安备 11010502051620号
