Prediction of outflow temperature of reservoir based on theory-guided machine learning models and optimization of operation for improving outflow temperature DOI

Shiwei Yang,

Junguang Chen,

Ruifeng Liang

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: unknown, P. 143652 - 143652

Published: Sept. 1, 2024

Language: Английский

Eco-friendly dredging methods of changing fluvial landforms for enhancing hydraulic habitat quality and river corridor continuum DOI
Shang‐Shu Shih, Chen-Yu Lee

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 936, P. 173439 - 173439

Published: May 23, 2024

Language: Английский

Citations

2
Quantitative determination of flow rate variations in reservoir Eco-scheduling: A case study of Yangqu dam in the upper yellow river DOI
Qiaoling Zhang, Zijun Liu,

Weiying Wang

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 365, P. 121620 - 121620

Published: June 27, 2024

Language: Английский

Citations

1
Comparative analysis of assessment models for rehabilitation potential of fish habitat DOI Creative Commons
Jaeseung Seo, Dong-Hyun Kim, Junhyeong Lee

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 161, P. 112003 - 112003

Published: April 1, 2024

A simple model that can assess the river rehabilitation using potential index (RPI) of fish habitat has been developed. This calculates RPI three indicators: suitability (HSI), niche breadth (NB), and overlap (NO). These indicators were estimated by environmental factors affect in then was obtained combining indicators. However, showed some limitations. For example, representative NO summing each NO, which does not reflect difference number species rivers. study improved estimation method averaged consider different kinds river. In addition, previous used standardization for making indicator values range 0 to 1. standardized distort relative size when we compare with original data. this study, have selected alternative methods calculate indicators, eliminating need standardization. Along these improvements, developed a new reviewing various selecting proper ones. The RPIs two models abundance from 57 sites Han river, Geum Nakdong Korea. We compared results existing root mean square error (RMSE) absolute deviation (MAD). reduced uncertainty enhanced applicability comparison model.

Language: Английский

Citations

0
Prediction of outflow temperature of reservoir based on theory-guided machine learning models and optimization of operation for improving outflow temperature DOI

Shiwei Yang,

Junguang Chen,

Ruifeng Liang

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: unknown, P. 143652 - 143652

Published: Sept. 1, 2024

Language: Английский

Citations

0