A critical review on low salinity waterflooding for enhanced oil recovery: Experimental studies, simulations, and field applications

Geoenergy Science and Engineering, Journal Year: 2023, Volume and Issue: 227, P. 211936 - 211936

Published: May 22, 2023

Language: Английский

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Estuary salinity prediction using machine learning: case study in the Hau estuary in Mekong River, Vietnam

Water Science & Technology Water Supply, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 15, 2025

ABSTRACT The prediction of saltwater intrusion in estuaries plays an important role, supporting decision-makers or farmers building strategies, and also, policies made for agricultural development water resource management. objective this study is to develop machine learning models, namely gated recurrent unit (GRU), GRU-GWO (grey wolf optimiser), GRU-SFO (sailfish optimiser algorithm) predict 1, 7, 15, 30 days ahead the Mekong estuary Vietnam. Several statistical indices, root mean square error (RMSE), absolute (MAE), coefficient determination (R2), were applied evaluate accuracy model. results showed that GWO SFO optimisation algorithms successfully improved GRU model intrusion. For a one day forecast, R2 value proposed models ranged from 0.89 0.91, seven it 0.81 0.85, 15-day 0.67 0.76, 30-day 0.52 0.55. indicated ability

Language: Английский

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Prognostic and Health Management of Critical Aircraft Systems and Components: An Overview

Sensors, Journal Year: 2023, Volume and Issue: 23(19), P. 8124 - 8124

Published: Sept. 27, 2023

Prognostic and health management (PHM) plays a vital role in ensuring the safety reliability of aircraft systems. The process entails proactive surveillance evaluation state functional effectiveness crucial subsystems. principal aim PHM is to predict remaining useful life (RUL) subsystems proactively mitigate future breakdowns order minimize consequences. achievement this objective helped by employing predictive modeling techniques doing real-time data analysis. incorporation prognostic methodologies utmost importance execution condition-based maintenance (CBM), strategic approach that emphasizes prioritization repairing components have experienced quantifiable damage. Multiple are employed support advancement prognostics for aviation systems, encompassing physics-based modeling, data-driven techniques, hybrid prognosis. These enable prediction mitigation failures identifying relevant indicators. Despite promising outcomes sector pertaining implementation PHM, there exists deficiency research concerning efficient integration applications. primary paper provide thorough analysis current advancements with specific focus on prominent algorithms their practical applications challenges. concludes providing detailed prospective directions within field.

Language: Английский

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Leveraging machine learning algorithms for improved disaster preparedness and response through accurate weather pattern and natural disaster prediction

Frontiers in Environmental Science, Journal Year: 2023, Volume and Issue: 11

Published: Nov. 2, 2023

Globally, communities and governments face growing challenges from an increase in natural disasters worsening weather extremes. Precision disaster preparation is crucial responding to these issues. The revolutionary influence that machine learning algorithms have strengthening catastrophe response systems thoroughly explored this paper. Beyond a basic summary, the findings of our study are striking demonstrate sophisticated powers forecasting variety patterns anticipating range catastrophes, including heat waves, droughts, floods, hurricanes, more. We get practical insights into complexities applications, which support enhanced effectiveness predictive models preparedness. paper not only explains theoretical foundations but also presents proof significant benefits provide. As result, results open door for governments, businesses, people make wise decisions. These accurate predictions catastrophes emerging may be used implement pre-emptive actions, eventually saving lives reducing severity damage.

Language: Английский

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Physics-based Bayesian linear regression model for predicting length of mixed oil

Geoenergy Science and Engineering, Journal Year: 2023, Volume and Issue: 223, P. 211466 - 211466

Published: Jan. 26, 2023

Language: Английский

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Multi-step ahead dissolved oxygen concentration prediction based on knowledge guided ensemble learning and explainable artificial intelligence

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 636, P. 131297 - 131297

Published: May 9, 2024

Language: Английский

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Machine learning in microalgae biotechnology for sustainable biofuel production: Advancements, applications, and prospects

Bioresource Technology, Journal Year: 2024, Volume and Issue: unknown, P. 131549 - 131549

Published: Sept. 1, 2024

Language: Английский

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Novel robust Elman neural network-based predictive models for bubble point oil formation volume factor and solution gas–oil ratio using experimental data

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(23), P. 14503 - 14526

Published: May 8, 2024

Language: Английский

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Concatenating data-driven and reduced-physics models for smart production forecasting

Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(2)

Published: Feb. 1, 2025

Language: Английский

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Innovative screening for functional improved aromatic amine derivatives: Toxicokinetics, free radical oxidation pathway and carcinogenic adverse outcome pathway

Journal of Hazardous Materials, Journal Year: 2023, Volume and Issue: 454, P. 131541 - 131541

Published: April 30, 2023

Language: Английский

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