Hybrid WT–CNN–GRU-based model for the estimation of reservoir water quality variables considering spatio-temporal features

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 358, P. 120756 - 120756

Published: April 9, 2024

Language: Английский

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Machine learning approaches for estimating interfacial tension between oil/gas and oil/water systems: a performance analysis

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 9, 2024

Abstract Interfacial tension (IFT) is a key physical property that affects various processes in the oil and gas industry, such as enhanced recovery, multiphase flow, emulsion stability. Accurate prediction of IFT essential for optimizing these increasing their efficiency. This article compares performance six machine learning models, namely Support Vector Regression (SVR), Random Forests (RF), Decision Tree (DT), Gradient Boosting (GB), Catboosting (CB), XGBoosting (XGB), predicting between oil/gas oil/water systems. The models are trained tested on dataset contains input parameters influence IFT, gas-oil ratio, formation volume factor, density, etc. results show SVR Catboost achieve highest accuracy prediction, with an R-squared value 0.99, while outperforms Oil/Water 0.99. study demonstrates potential reliable resilient tool industry. findings this can help improve understanding optimization forecasting facilitate development more efficient reservoir management strategies.

Language: Английский

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Machine learning for predicting concrete carbonation depth: A comparative analysis and a novel feature selection

Construction and Building Materials, Journal Year: 2024, Volume and Issue: 417, P. 135331 - 135331

Published: Feb. 1, 2024

Language: Английский

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Simulating daily PM2.5 concentrations using wavelet analysis and artificial neural network with remote sensing and surface observation data

Chemosphere, Journal Year: 2023, Volume and Issue: 340, P. 139886 - 139886

Published: Aug. 21, 2023

Language: Английский

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A multi-model data fusion methodology for reservoir water quality based on machine learning algorithms and bayesian maximum entropy

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 416, P. 137885 - 137885

Published: June 28, 2023

Language: Английский

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An ensemble model for monthly runoff prediction using least squares support vector machine based on variational modal decomposition with dung beetle optimization algorithm and error correction strategy

Journal of Hydrology, Journal Year: 2023, Volume and Issue: 629, P. 130558 - 130558

Published: Dec. 7, 2023

Language: Английский

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A coupled model to improve river water quality prediction towards addressing non-stationarity and data limitation

Water Research, Journal Year: 2023, Volume and Issue: 248, P. 120895 - 120895

Published: Nov. 20, 2023

Language: Английский

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Impact on nonlinear runoff of LID facilities and parameter response in the TVGM model

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132780 - 132780

Published: Jan. 1, 2025

Language: Английский

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Developing sustainable strategies by LID optimization in response to annual climate change impacts

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 416, P. 137931 - 137931

Published: June 28, 2023

Language: Английский

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Forecasting water quality variable using deep learning and weighted averaging ensemble models

Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: 30(59), P. 124316 - 124340

Published: Nov. 24, 2023

Language: Английский

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