Interpretable Machine Learning Approach to Predict Hepatitis C Virus NS5B Inhibitor Activity Using Voting-Based LightGBM and SHAP

Intelligent Systems with Applications, Год журнала: 2025, Номер 25, С. 200481 - 200481

Опубликована: Янв. 15, 2025

Язык: Английский

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Impact of inhibition mechanisms, automation, and computational models on the discovery of organic corrosion inhibitors

Progress in Materials Science, Год журнала: 2024, Номер unknown, С. 101392 - 101392

Опубликована: Окт. 1, 2024

Язык: Английский

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Dual-Stage Stacking Machine Learning Method Considering Virtual Sample Generation for the Prediction of ZIF-8′ BET Specific Surface Area with Experimental Validation

Langmuir, Год журнала: 2025, Номер unknown

Опубликована: Янв. 17, 2025

The widespread application of metal-organic frameworks (MOFs) in wastewater and gas treatment has created an increasing demand for accurate rapid assessment their BET specific surface area. However, experimental methods acquiring sufficient statistical data are often costly time-consuming. Therefore, this study proposes a dual-stage stacking model with Gaussian mixture model-virtual sample generation (GMM-VSG) technology the area prediction. In study, 90 real samples were selected from MOF database 300 virtual generated. performance on both was evaluated by using four machine learning models, including Bayesian regression (Bayes), adaptive boosting (AdaBoost), random forest (RF), extreme gradient (XGBoost). Subsequently, three best-performing models linear constructing two-stage model, R2 value 0.974. Finally, conditions adjusted based feature importance analysis during validation process, result shows that prediction accuracy is 0.943. This contributes to development more efficient evaluation methods.

Язык: Английский

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Multi-objective optimization in machine learning assisted materials design and discovery

Journal of Materials Informatics, Год журнала: 2025, Номер 5(2)

Опубликована: Март 24, 2025

Over the past decades, machine learning has kept playing an important role in materials design and discovery. In practical applications, usually need to fulfill requirements of multiple target properties. Therefore, multi-objective optimization based on become one most promising directions. This review aims provide a detailed discussion learning-assisted discovery combined with recent research progress. First, we briefly introduce workflow learning. Then, Pareto fronts corresponding algorithms are summarized. Next, strategies demonstrated, including front-based strategy, scalarization function, constraint method. Subsequently, progress is summarized different discussed. Finally, propose future directions for learning-based materials.

Язык: Английский

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Corrosion protective and antibacterial epoxy coating via benzyldisulfide‑sulfur-doped graphene oxide with machine-learning simulation support

Progress in Organic Coatings, Год журнала: 2024, Номер 194, С. 108604 - 108604

Опубликована: Июнь 15, 2024

Язык: Английский

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Machine learning for pyrimidine corrosion inhibitor small dataset

Theoretical Chemistry Accounts, Год журнала: 2024, Номер 143(8)

Опубликована: Авг. 1, 2024

Язык: Английский

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State-of-the-art progress on artificial intelligence and machine learning in accessing molecular coordination and adsorption of corrosion inhibitors

Applied Physics Reviews, Год журнала: 2025, Номер 12(1)

Опубликована: Янв. 6, 2025

Artificial intelligence (AI) and machine learning (ML) have attracted the interest of research community in recent years. ML has found applications various areas, especially where relevant data that could be used for algorithm training retraining are available. In this review article, been discussed relation to its corrosion science, monitoring control. tools techniques, structure modeling methods, were thoroughly discussed. Furthermore, detailed inhibitor design/modeling coupled with associated limitations future perspectives reported.

Язык: Английский

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Beyond spatial neighbors: Utilizing multivariate transfer entropy for interpretable graph-based spatio–temporal forecasting

Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 146, С. 110161 - 110161

Опубликована: Фев. 17, 2025

Язык: Английский

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An active learning framework assisted development of corrosion risk assessment strategies for offshore pipelines

Process Safety and Environmental Protection, Год журнала: 2024, Номер unknown

Опубликована: Окт. 1, 2024

Язык: Английский

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Virtual sample generation for small sample learning: a survey, recent developments and future prospects

Neurocomputing, Год журнала: 2024, Номер unknown, С. 128934 - 128934

Опубликована: Ноя. 1, 2024

Язык: Английский

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