The progress of machine learning (ML) in the past years has opened up new opportunities
to the field of gas turbine (GT) modelling. However, successful implementation of ML …

Abstract Recent advancements in Information Technology (IT) have engendered the rapid
production of big data, as enormous volumes of data with high dimensional features grow …

This study proposes a new hybrid deep learning (DL) model, the called CSVR, for Global
Solar Radiation (GSR) predictions by integrating Convolutional Neural Network (CNN) with …

The prevalence of diabetes has been increasing in recent years, and previous research has
found that machine-learning models are good diabetes prediction tools. The purpose of this …

Controlling carbon dioxide produced from green waste composting is a vital issue in
response to carbon neutralization. However, there are few computational methods for …

Particle swarm optimization (PSO) is a promising method for feature selection. When using
PSO to solve the feature selection problem, the probability of each feature being selected …

In machine learning and pattern recognition tasks, classification performance is often
degraded due to the existence of irrelevant and redundant features, especially for high …

Generally, for high-dimensional datasets, only some features are relevant, while others are
irrelevant or redundant. In the machine learning field, the use of a strategy for eliminating …

In high-dimensional gene expression data, selecting an optimal subset of genes is crucial
for achieving high classification accuracy and reliable diagnosis of diseases. This paper …

Discretization-based feature selection (DBFS) approaches have shown interesting results
when using several metaheuristic algorithms, such as particle swarm optimization (PSO) …