This study proposes a state monitoring algorithm combining a convolutional neural network (CNN) with a random forest (RF) for data missing scenarios. CNN algorithm is designed to extract the ...

More alike than we think: UVA researchers find a similar pattern of distribution among plants, animals and microbes. (Illustration by John DiJulio, University Communications) ...

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 ...

Background and Aims: This study aimed to develop an interpretable random forest model for predicting severe acute pancreatitis (SAP). Methods: Clinical and laboratory data of 648 patients with acute ...

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 ...

Some top data mining algorithms, as ensemble classifiers, may be inefficient to very large data set. This paper makes an initial proposal of a distributed ensemble classifier algorithm based on the ...