Analysis and machine-learning-based prediction of beach accidents on a recreational beach in China DOI Open Access
Yuan Li, Jiqiang Tang, Chi Zhang

et al.

Anthropocene Coasts, Journal Year: 2024, Volume and Issue: 7(1)

Published: Dec. 30, 2024

Abstract Beachgoers are sometimes exposed to coastal hazards, yet comprehensive analyses of characteristics and potential factors for beach accidents rarely reported in China. In this study, information on was collected a recreational from 2004 2022 by searching the web or apps. The were therefore analysed terms age, gender, activity beachgoers. resolved environmental aspects meteorology, waves, tides, morphology. Results show that mainly occur summer, with highest occurrence afternoon evening. number male beachgoers is five times higher than females. 90% when at high-risk level rip currents, providing evidence accuracy risk map built previous study. Three machine learning models, i.e., Support Vector Machine, Random Forest, BP Neural Networks, trained predict accidents. performances these three algorithms evaluated precision, recall, F1 score. Machine Networks significantly outperform Forest prediction. predicting "safe" "dangerous" classes approximately 80% model. This paper provides preliminary study based accident prediction specific tourist beach. future, will be applied throughout mainland

Language: Английский

Enhancing Water Level Prediction Using Ensemble Machine Learning Models: A Comparative Analysis DOI
Saleh Alsulamy, Vijendra Kumar, Özgür Kişi

et al.

Water Resources Management, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 11, 2025

Language: Английский

Citations

3
Comparison of extreme gradient boosting, deep learning, and self-organizing map methods in predicting groundwater depth DOI
Vahid Gholami, Mohammad Reza Khaleghi, E. Taghvaye Salimi

et al.

Environmental Earth Sciences, Journal Year: 2025, Volume and Issue: 84(7)

Published: March 21, 2025

Language: Английский

Citations

0
Long-term prediction of Poyang Lake water level by combining multi-scale isometric convolution network with quantile regression DOI
Ying Jian, Yong Zheng,

Gang Li

et al.

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 59, P. 102365 - 102365

Published: April 17, 2025

Language: Английский

Citations

0
Water Resources Quality Indicators Monitoring by Nonlinear Programming and Simulated Annealing Optimization with Ensemble Learning Approaches DOI
Mojtaba Poursaeid, Amir Hossein Poursaeed, Saeid Shabanlou

et al.

Water Resources Management, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 31, 2024

Language: Английский

Citations

3
The Response to Hydrological Regime Change of Nitrogen Transformation Processes at the Sediment‐Water Interface of Seasonal Floodplain Lakes: Insights From the Yangtze River‐Poyang Lake System DOI Creative Commons
Zhongtian Zhang, Guangqiu Jin, Hongwu Tang

et al.

Water Resources Research, Journal Year: 2025, Volume and Issue: 61(4)

Published: April 1, 2025

Abstract Poyang Lake, the largest freshwater lake in China and a globally significant wetland, is intricately connected to hydrological dynamics of Yangtze River via complex river‐lake exchange system. This system generates unique seasonal fluctuations, forming distinctive system, which influences hydrodynamic processes across floodplains. Recent years have witnessed alterations patterns River, notably water levels, thereby impacting nutrient such as nitrogen transformation at sediment‐water interface Lake. study establishes coupled model integrating hydrodynamics elucidate impacts regime on Lake after operation Three Gorges Dam. Findings reveal spatiotemporal variations both hydraulics within Notably, recharge rate between surface groundwater experiences substantial shift, surpassing 60%. Furthermore, nitrification escalates by 28.5%, denitrification increases 21.3% owing pronounced regime. However, this intensified does not translate enhanced efficiency, efficiency declines 72.3% its original rate. research provides theoretical framework for understanding ecological environmental human interventions highlights implications managing other floodplains lakes globally, Amazon Mekong face similar challenges ecosystem health.

Language: Английский

Citations

0
Relationships between hydrological connectivity and river-lake ecospace in urban-rural areas DOI Creative Commons
Jianchuan Zhou, Hang Yin, Yeling Liu

et al.

HydroResearch, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

Citations

0
Different Time-Increment Rainfall Prediction Models: a Machine Learning Approach Using Various Input Scenarios DOI
Amir Rahimi, Noor Kh. Yashooa, Ali Najah Ahmed

et al.

Water Resources Management, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 3, 2024

Language: Английский

Citations

1
Analysis and machine-learning-based prediction of beach accidents on a recreational beach in China DOI Open Access
Yuan Li, Jiqiang Tang, Chi Zhang

et al.

Anthropocene Coasts, Journal Year: 2024, Volume and Issue: 7(1)

Published: Dec. 30, 2024

Abstract Beachgoers are sometimes exposed to coastal hazards, yet comprehensive analyses of characteristics and potential factors for beach accidents rarely reported in China. In this study, information on was collected a recreational from 2004 2022 by searching the web or apps. The were therefore analysed terms age, gender, activity beachgoers. resolved environmental aspects meteorology, waves, tides, morphology. Results show that mainly occur summer, with highest occurrence afternoon evening. number male beachgoers is five times higher than females. 90% when at high-risk level rip currents, providing evidence accuracy risk map built previous study. Three machine learning models, i.e., Support Vector Machine, Random Forest, BP Neural Networks, trained predict accidents. performances these three algorithms evaluated precision, recall, F1 score. Machine Networks significantly outperform Forest prediction. predicting "safe" "dangerous" classes approximately 80% model. This paper provides preliminary study based accident prediction specific tourist beach. future, will be applied throughout mainland

Language: Английский

Citations

0