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 …

Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …

The vast majority of today's data is collected and stored in enormous databases with a wide
range of characteristics that have little to do with the overarching goal concept. Feature …

In recent years, swarm intelligence algorithms have received extensive attention and
research. Swarm intelligence algorithms are a biological heuristic method, which is widely …

Fuel cells are considered as new kinds of clean energy sources. This study presents a
method for optimal unknown parameters identification of a Solid Oxide Fuel Cell (SOFC) …

A novel bio-inspired algorithm called Orca Predation Algorithm (OPA) is proposed in this
paper. OPA simulates the hunting behavior of orcas and abstracts it into several …

The rapid expansion of information science has caused the issue of “the curse of
dimensionality”, which will negatively affect the performance of the machine learning model …

This survey is an effort to provide a research repository and a useful reference for
researchers to guide them when planning to develop new Nature-inspired Algorithms …

This paper proposes a binary version of Horse herd Optimization Algorithm (HOA) to tackle
Feature Selection (FS) problems. This algorithm mimics the conduct of a pack of horses …

Abstract Software Fault Prediction (SFP) is an important process to detect the faulty
components of the software to detect faulty classes or faulty modules early in the software …