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 whale optimization algorithm (WOA) is a prominent problem solver which is broadly
applied to solve NP-hard problems such as feature selection. However, it and most of its …

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 this paper, a new bio-inspired metaheuristic algorithm called Zebra Optimization
Algorithm (ZOA) is developed; its fundamental inspiration is the behavior of zebras in nature …

Overbreak is a detrimental phenomenon caused by tunnel blasting, which can lead to
increased time and cost in the construction schedule. It is very important to establish a model …

As the number and cleverness of cyber-attacks keep increasing rapidly, it's more important
than ever to have good ways to detect and prevent them. Recognizing cyber threats quickly …

Water contamination with colours and heavy metals from textile effluents has harmed the
ecology and food chain, with mutagenic and carcinogenic effects on human health. As a …

The main objective of feature selection is to improve learning performance by selecting
concise and informative feature subsets, which presents a challenging task for machine …

Dipper throated optimization (DTO) algorithm is a novel with a very efficient metaheuristic
inspired by the dipper throated bird. DTO has its unique hunting technique by performing …