Artificial intelligence: A key fulcrum for addressing complex environmental health issues

Environment International, Год журнала: 2025, Номер unknown, С. 109389 - 109389

Опубликована: Март 1, 2025

Язык: Английский

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Artificial Intelligence in Hydrology: Advancements in Soil, Water Resource Management, and Sustainable Development

Sustainability, Год журнала: 2025, Номер 17(5), С. 2250 - 2250

Опубликована: Март 5, 2025

Hydrology relates to many complex challenges due climate variability, limited resources, and especially, increased demands on sustainable management of water soil. Conventional approaches often cannot respond the integrated complexity continuous change inherent in system; hence, researchers have explored advanced data-driven solutions. This review paper revisits how artificial intelligence (AI) is dramatically changing most important facets hydrological research, including soil land surface modeling, streamflow, groundwater forecasting, quality assessment, remote sensing applications resources. In AI techniques could further enhance accuracy texture analysis, moisture estimation, erosion prediction for better management. Advanced models also be used as a tool forecast streamflow levels, therefore providing valuable lead times flood preparedness resource planning transboundary basins. quality, AI-driven methods improve contamination risk enable detection anomalies, track pollutants assist treatment processes regulatory practices. combined with open new perspectives monitoring resources at spatial scale, from forecasting storage variations. paper’s synthesis emphasizes AI’s immense potential hydrology; it covers latest advances future prospects field ensure

Язык: Английский

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Application of an improved LSTM model based on FECA and CEEMDAN VMD decomposition in water quality prediction

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 14, 2025

To address the limitations of existing water quality prediction models in handling non-stationary data and capturing multi-scale features, this study proposes a hybrid model integrating Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Variational (VMD), Long Short-Term Memory Network (LSTM), Frequency-Enhanced Channel Attention (FECA). The aims to improve accuracy robustness for complex dynamics, which is critical environmental protection sustainable resource management. First, CEEMDAN Sample Entropy (SE) were used decompose raw into interpretable components filter noise. Then, VMD-enhanced LSTM architecture embedded FECA was developed adaptively prioritize frequency-specific thereby improving model's ability handle nonlinear patterns. Results show that successful predicting all six indicators: NH₃-N (ammonia nitrogen), DO (dissolved oxygen), pH, TN (total TP phosphorus), CODMn (chemical oxygen demand, permanganate method). achieved Nash-Sutcliffe Efficiency (NSE) values ranging from 0.88 0.99. Using dissolved (DO) as an example, reduced Mean Absolute Percentage Error (MAPE) by 0.12% increased coefficient determination (R2) 0.20% compared baseline methods. This work provides robust framework real-time monitoring supports decision making pollution control ecosystem

Язык: Английский

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Carbon source dosage intelligent determination using a multi-feature sensitive back propagation neural network model

Journal of Environmental Management, Год журнала: 2025, Номер 376, С. 124341 - 124341

Опубликована: Фев. 15, 2025

Язык: Английский

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Multi-task neural network combined with multi-source data for inversion of discrete fracture network apertures: Aperture-XNET

Journal of Hydrology, Год журнала: 2025, Номер unknown, С. 133584 - 133584

Опубликована: Май 1, 2025

Язык: Английский

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Optimization of graph wavenet model for dissolved oxygen prediction using self-distillation and whale optimization algorithm

Journal of Water Process Engineering, Год журнала: 2025, Номер 75, С. 108013 - 108013

Опубликована: Май 29, 2025

Язык: Английский

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Development of Water Quality Prediction Model Using LTSF-Linear and Complete Ensemble Empirical Mode Decomposition

Desalination and Water Treatment, Год журнала: 2025, Номер unknown, С. 101254 - 101254

Опубликована: Июнь 1, 2025

Язык: Английский

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