A novel operational water quality mobile prediction system with LSTM-Seq2Seq model DOI

Lizi Xie,

Yanxin Zhao, Fang Pan

et al.

Environmental Modelling & Software, Journal Year: 2024, Volume and Issue: 185, P. 106290 - 106290

Published: Dec. 9, 2024

Language: Английский

Recent development on drought propagation: A comprehensive review DOI

Zhou Zhaoqiang,

Ping Wang,

Li Linqi

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: unknown, P. 132196 - 132196

Published: Oct. 1, 2024

Language: Английский

Citations

7
Exploring the influence of training sampling strategies on time-series deep learning model in hydrology DOI
Sung-Hyun Yoon, Kuk‐Hyun Ahn

Journal of Hydrology, Journal Year: 2025, Volume and Issue: 653, P. 132774 - 132774

Published: Jan. 31, 2025

Language: Английский

Citations

0
A visualizable deep learning model for multiscale precipitation-driven karst spring discharge DOI

Huiqing Hao,

Yonghong Hao, Chunmei Ma

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 133168 - 133168

Published: March 1, 2025

Language: Английский

Citations

0
Streamflow regime-based classification and hydrologic similarity analysis of catchment behavior using differentiable modeling with multiphysics outputs DOI

Yuqian Hu,

Heng Li, Chunxiao Zhang

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: 653, P. 132766 - 132766

Published: Jan. 29, 2025

Language: Английский

Citations

0
Enhancing runoff simulation by combining superflex with deep learning methods in China's Qinghai Lake Basin, Northeast Tibetan Plateau DOI

Kaixun Liu,

Na Li, Sihai Liang

et al.

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 59, P. 102331 - 102331

Published: March 26, 2025

Language: Английский

Citations

0
A Robust Multi-Model Framework for Groundwater Level Prediction: The BFSA-MVMD-GRU-RVM Model DOI Creative Commons
Akram Seifi, Sharareh Pourebrahim,

Mohammad Ehteram

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 103250 - 103250

Published: Oct. 1, 2024

Language: Английский

Citations

2
Comparative analysis of machine learning models and explainable AI for agriculture drought prediction: A case study of the Ta-pieh mountains DOI Creative Commons
Lichang Xu, Shaowei Ning, Xiaoyan Xu

et al.

Agricultural Water Management, Journal Year: 2024, Volume and Issue: 306, P. 109176 - 109176

Published: Nov. 17, 2024

Language: Английский

Citations

2
Integrated learning model for water intake capacity of Tyrolean weirs under supercritical flow DOI Creative Commons
Guiying Shen, Yufeng Liang, Abbas Parsaie

et al.

Journal of Hydroinformatics, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 30, 2024

ABSTRACT Tyrolean weir can be used as an effective solution to address floatation and sediment deposition in runoff hydropower stations. To improve the efficiency accuracy of calculating this structure's water intake capacity. The integrated learning algorithm random forest (RF), firefly (FA), exponential distribution (EDO) are utilized develop that for Cd (qw)i/(qw)T prediction models. Sobol's method SHAP theory introduced analyze above parameters quantitatively qualitatively. It is shown EDO-RF optimal model weir's discharge coefficient Froude number Fr has greatest influence on results; when < 30, greater negative results. When > positive FA-RF capture capacity (qw)i/(qw)T, with ratio bar length spacing L/e being largest; 20, more significant impact

Language: Английский

Citations

0
A novel operational water quality mobile prediction system with LSTM-Seq2Seq model DOI

Lizi Xie,

Yanxin Zhao, Fang Pan

et al.

Environmental Modelling & Software, Journal Year: 2024, Volume and Issue: 185, P. 106290 - 106290

Published: Dec. 9, 2024

Language: Английский

Citations

0