The increasing energy prices and pollutants from fossil fuels that threaten the climate, there
is a growing preference for renewable energy. The implementation of hybrid renewable …

Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …

Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …

This paper proposes a Sine Cosine hybrid optimization algorithm with Modified Whale
Optimization Algorithm (SCMWOA). The goal is to leverage the strengths of WOA and SCA …

Feature selection is a required preprocess stage in most of the data mining tasks. This paper
presents an improved Harris hawks optimization (HHO) to find high-quality solutions for …

Feature selection, an optimization problem, becomes an important pre-process tool in data
mining, which simultaneously aims at minimizing feature-size and maximizing model …

Recently, many optimization algorithms have been applied for Feature selection (FS)
problems and show a clear outperformance in comparison with traditional FS methods …

Introduction: In pattern recognition and data mining, feature selection is one of the most
crucial tasks. To increase the efficacy of classification algorithms, it is necessary to identify …

In this article, an improved variant of the grey wolf optimizer (GWO) named gaze cues
learning-based grey wolf optimizer (GGWO) is proposed. The main intentions are to reduce …

Because of their high dimensionality, dealing with large datasets can hinder the data mining
process. Thus, the feature selection is a pre-process mandatory phase for reducing the …