Load forecasting, a crucial aspect of energy management, involves predicting the future electricity demand based on historical data. In the context of monthly time series analysis, this study focuses ...

This paper proposes a Random Forest (RF) machine learning algorithm-based prediction model for the state of charge (SoC) level of lithium-ion batteries for electric vehicles. To show the effectiveness ...

Machine Learning Models Random Forest Random Forest is a versatile machine learning algorithm that is effective in handling large datasets with multiple features. By constructing a multitude of ...

In the second part of the analysis, three machine learning models—Logistic Regression, Random Forest, and XGBoost—were implemented for predictive performance. Logistic Regression outperformed others ...

This paper proposes a Random Forest grid fault prediction model based on Genetic Algorithm optimization (GA-RF) to classify the grid fault types, which improves the distribution network fault ...

Keywords: colorectal polyps, random forests, machine learning, colorectal cancer prevention, risk prediction model, artificial intelligence Citation: Avram M-F, Lupa N, Koukoulas D, Lazăr D-C, Mariș M ...

This article explores the top 10 ML algorithms essential for quality assurance, from Decision Trees for defect prediction to Neural Networks for automated test generation, helping test engineers ...