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 …

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 …

In the past decades, the rapid growth of computer and database technologies has led to the
rapid growth of large-scale datasets. On the other hand, data mining applications with high …

Metaheuristics are an impressive area of research with extremely important improvements in
the solution of intractable optimization problems. Major advances have been made since the …

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 …

Support vector machine (SVM) is a widely used pattern classification method that its
classification accuracy is greatly influenced by both kernel parameter setting and feature …

The advance rate (AR) of a tunnel boring machine (TBM) in hard rock condition is a key
parameter for the successful accomplishment of a tunneling project, and the proper and …

The emergence of fuzzy sets makes job-shop scheduling problem (JSSP) become better
aligned with the reality. This article addresses the JSSP with fuzzy execution time and fuzzy …

The emergence of the 2019 novel coronavirus (COVID-19) which was declared a pandemic
has spread to 210 countries worldwide. It has had a significant impact on health systems …