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 ...

Most of the existing deep learning prediction algorithms are based on deep neural networks, which are suitable for continuous process modelling, but are not ideal for discrete processes such as ...

Objectives We used machine learning algorithms to track how the ranks of importance and the survival outcome of four socioeconomic determinants (place of residence, mother’s level of education, wealth ...

Random Forest (RF) Machine Learning (ML) Algorithm The RF ML algorithm is based on an ensemble of decision trees that are randomly generated from a set of input (or predictor) features, and the output ...

The paper presents the implementation of random forest algorithm applied to decision making, when designing power electronic converters. The algorithm is used to aid topology selection and more ...

Abstract In this paper, sixty-eight research articles published between 2000 and 2017 as well as textbooks which employed four classification algorithms: K-Nearest-Neighbor (KNN), Support Vector ...

This is one of the best introductions to Random Forest algorithm. The author introduces the algorithm with a real-life story and then provides applications in four different fields to help beginners ...