Analysis and prediction of water quality using deep learning and auto deep learning techniques

The Science of The Total Environment, Год журнала: 2022, Номер 821, С. 153311 - 153311

Опубликована: Янв. 19, 2022

Язык: Английский

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A novel model for water quality prediction caused by non-point sources pollution based on deep learning and feature extraction methods

Journal of Hydrology, Год журнала: 2022, Номер 612, С. 128081 - 128081

Опубликована: Июнь 18, 2022

Язык: Английский

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Artificial Neural Network Modeling for the Prediction, Estimation, and Treatment of Diverse Wastewaters: A Comprehensive Review and Future Perspective

Chemosphere, Год журнала: 2024, Номер 362, С. 142860 - 142860

Опубликована: Июль 15, 2024

Язык: Английский

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A novel long short-term memory artificial neural network (LSTM)-based soft-sensor to monitor and forecast wastewater treatment performance

Journal of Water Process Engineering, Год журнала: 2023, Номер 54, С. 104041 - 104041

Опубликована: Июль 19, 2023

Язык: Английский

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Prediction of wastewater treatment plant performance through machine learning techniques

Desalination and Water Treatment, Год журнала: 2024, Номер 319, С. 100524 - 100524

Опубликована: Июнь 11, 2024

This study investigates the use of developed machine learning techniques for modeling performance AlHayer, Saudi Arabia, wastewater treatment plant (ALWTP). Three physio-chemical characteristics were measured and predicted, including chemical oxygen demand (COD), biological (BOD), suspended solids (SS), at ALWTP. The pre-evaluation collected data revealed effective capabilities ALWTP removal solids, organic, nutrient pollutants. To estimate ALWATP, four evaluated compared. Logistic regression (LR), random forest (RF), gradient boosting (GB), support vector (SVR) designed. evaluation proposed models showed RF outperformed other estimating COD SS with accuracy 91 % 95 in terms coefficient determination (R2); however, GB was found best, 92 %, detecting BOD ALWATP. indicates ensemble models, GB, can be considered a superiority soft solution plant.

Язык: Английский

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Artificial intelligence driven advances in wastewater treatment: Evaluating techniques for sustainability and efficacy in global facilities

Desalination and Water Treatment, Год журнала: 2024, Номер 320, С. 100618 - 100618

Опубликована: Июль 17, 2024

Язык: Английский

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Development of an embedded molecular structure-based model for prediction of micropollutant treatability in a drinking water treatment plant by machine learning from three years monitoring data

Water Research, Год журнала: 2023, Номер 239, С. 120037 - 120037

Опубликована: Май 2, 2023

Язык: Английский

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An integral and multidimensional review on multi-layer perceptron as an emerging tool in the field of water treatment and desalination processes

Desalination, Год журнала: 2024, Номер 586, С. 117849 - 117849

Опубликована: Июнь 15, 2024

Язык: Английский

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Water quality prediction of artificial intelligence model: a case of Huaihe River Basin, China

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(10), С. 14610 - 14640

Опубликована: Янв. 26, 2024

Язык: Английский

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Forecasting influent wastewater quality by chaos coupled machine learning optimized with Bayesian algorithm

Journal of Water Process Engineering, Год журнала: 2024, Номер 61, С. 105306 - 105306

Опубликована: Апрель 16, 2024

Язык: Английский

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