Optimization is a method which is used in every field, such as engineering, space, finance,
fashion market, mass communication, travelling, and also in our daily activities. In every …

The efficiency and the effectiveness of a machine learning (ML) model are greatly influenced
by feature selection (FS), a crucial preprocessing step in machine learning that seeks out the …

Abstract Feature Subset Selection (FSS) is an NP-hard problem to remove redundant and
irrelevant features particularly from medical data, and it can be effectively addressed by …

Moth-flame optimization (MFO) is a prominent problem solver with a simple structure that is
widely used to solve different optimization problems. However, MFO and its variants …

The worm gearbox is a power transmission system that has various applications in
industries. Being vital element of machinery, it becomes necessary to develop a robust fault …

In many disciplines, including pattern recognition, data mining, machine learning, image
analysis, and bioinformatics, data clustering is a common analytical tool for data statistics …

One of the most reliable deep learning approaches for image classification challenges is
deep Conventional Conv neural networks (DCNNs); however, identifying the appropriate …

Breast cancer (BC) is one of the leading causes of high mortality rates among women. An
early disease diagnosis is crucial in breast cancer's treatment for improving the survival rate …

Proposing a reliable feature selection approach is the primary stone for endorsing the
prediction performance; therefore, this paper proposes an enhanced optimization technique …

Gene selection (GS) is an important branch of interest within the field of feature selection,
which is widely used in cancer classification. It provides essential insights into the …