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An optimized NARX-based model for predicting thermal dynamics and heatwaves in rivers 期刊论文
SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 卷号: 926
收藏  |  浏览/下载：0/0  |  提交时间：2024/06/11
Prediction of daily river water temperatures using an optimized model based on NARX networks 期刊论文
ECOLOGICAL INDICATORS, 2024, 卷号: 161
作者:  Sun, Jiang;  Di Nunno, Fabio;  Sojka, Mariusz;  Ptak, Mariusz;  Luo, You;  Xu, Renyi;  Xu, Jing;  Luo, Yi;  Zhu, Senlin;  Granata, Francesco
收藏  |  浏览/下载：2/0  |  提交时间：2024/06/11
Prediction of daily river water temperatures using an optimized model based on NARX networks 期刊论文
ECOLOGICAL INDICATORS, 2024, 卷号: 161
收藏  |  浏览/下载：0/0  |  提交时间：2024/06/11
Analysing the performance of the NARX model for forecasting the water level in the Chikugo River estuary, Japan 期刊论文
ENVIRONMENTAL RESEARCH, 2024, 卷号: 251
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Paddy straw as a biomass feedstock for the manufacturing of bioethanol using acid hydrolysis and parametric optimization through response surface methodology and an artificial neural network 期刊论文
BIOMASS CONVERSION AND BIOREFINERY, 2024
作者:  Jayakumar, Mani;  Thiyagar, Tissahlini;  Abo, Lata Deso;  Arumugasamy, Senthil Kumar;  Jabesa, Abdisa
收藏  |  浏览/下载：0/0  |  提交时间：2024/06/11
Paddy straw as a biomass feedstock for the manufacturing of bioethanol using acid hydrolysis and parametric optimization through response surface methodology and an artificial neural network 期刊论文
BIOMASS CONVERSION AND BIOREFINERY, 2024
收藏  |  浏览/下载：0/0  |  提交时间：2024/06/11
Using NARX neural network to forecast droughts and floods over Yangtze River Basin 期刊论文
Natural Hazards, 2021
作者:  Wang J.;  Chen Y.
收藏  |  浏览/下载：18/0  |  提交时间：2021/09/01
Droughts and floods  Global warming  GRACE  NARX  Total storage deficit index  
Determining China's CO2 emissions peak with a dynamic nonlinear artificial neural network approach and scenario analysis 期刊论文
ENERGY POLICY, 2019, 卷号: 128, 页码: 752-762
作者:  Xu, Guangyue;  Schwarz, Peter;  Yang, Hualiu
收藏  |  浏览/下载：2/0  |  提交时间：2019/11/07
Determining China's CO2 emissions peak with a dynamic nonlinear artificial neural network approach and scenario analysis 期刊论文
Energy Policy, 2019, 卷号: 128
作者:  Xu G.;  Schwarz P.;  Yang H.
收藏  |  浏览/下载：0/0  |  提交时间：2021/05/17