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

Journal of Environmental Management, Год журнала: 2024, Номер 358, С. 120756 - 120756

Опубликована: Апрель 9, 2024

Язык: Английский

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

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Янв. 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.

Язык: Английский

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

Construction and Building Materials, Год журнала: 2024, Номер 417, С. 135331 - 135331

Опубликована: Фев. 1, 2024

Язык: 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, Год журнала: 2023, Номер 340, С. 139886 - 139886

Опубликована: Авг. 21, 2023

Язык: 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, Год журнала: 2023, Номер 416, С. 137885 - 137885

Опубликована: Июнь 28, 2023

Язык: 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, Год журнала: 2023, Номер 629, С. 130558 - 130558

Опубликована: Дек. 7, 2023

Язык: Английский

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

Water Research, Год журнала: 2023, Номер 248, С. 120895 - 120895

Опубликована: Ноя. 20, 2023

Язык: Английский

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

Journal of Hydrology, Год журнала: 2025, Номер unknown, С. 132780 - 132780

Опубликована: Янв. 1, 2025

Язык: Английский

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

Journal of Cleaner Production, Год журнала: 2023, Номер 416, С. 137931 - 137931

Опубликована: Июнь 28, 2023

Язык: Английский

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

Environmental Science and Pollution Research, Год журнала: 2023, Номер 30(59), С. 124316 - 124340

Опубликована: Ноя. 24, 2023

Язык: Английский

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