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A deep learning-based hybrid approach for multi-time-ahead streamflow prediction in an arid region of Northwest China 期刊论文
发表期刊: HYDROLOGY RESEARCH. 出版年: 2024, 卷号: 55, 期号: 2, 页码: 180-204
作者:  Fang, J. J.;  Yang, Linshan;  Wen, Xiaohu;  Li, Weide;  Yu, Haijiao;  Zhou, Ting
收藏  |  浏览/下载：24/0  |  提交时间：2024/10/04
convolutional neural network (CNN)  long short-term memory (LSTM)  Shule River  streamflow prediction  Transformer  
Forecasting the potential of reclaimed water using signal decomposition and deep learning 期刊论文
发表期刊: JOURNAL OF WATER PROCESS ENGINEERING. 出版年: 2024, 卷号: 65
作者:  Chen, Yinglong;  Zhang, Hongling;  Peng, Jingkai;  Ma, Shilong;  Xu, Tengsheng;  Tang, Lian
收藏  |  浏览/下载：15/0  |  提交时间：2024/10/04
Complete ensemble empirical mode decompositionwith adaptivenoise(CEEMDAN)  Deep learning  Long short-term memory neural network (LSTM)  Convolutional neural network (CNN)  Reclaimed water volumes forecasting  
Brain-on-Cloud for automatic diagnosis of Alzheimer?s disease from 3D structural magnetic resonance whole-brain scans 期刊论文
发表期刊: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. 出版年: 2022, 卷号: 227
作者:  Tomassini, Selene;  Sbrollinia, Agnese;  Covellaa, Giacomo;  Sernani, Paolo;  Falcionelli, Nicola;  Millerb, Henning;  Morettinia, Micaela;  Burattinia, Laura;  Dragonia, Aldo Franco
收藏  |  浏览/下载：11/0  |  提交时间：2024/09/20
Alzheimer?s disease  Cloud computing  Computer-aided diagnosis  Convolutional LSTM  3D structural magnetic resonance  Supervised deep learning