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 …

Autonomous navigation is significant to UAVs, especially in disaster scenarios. A Hybrid
GWO and Differential Evolution (HGWODE) algorithm is developed to solve UAV path …

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

A cross-region prediction model named SeisEML (an acronym for Seismological Ensemble
Machine Learning) has been developed in this paper to predict the peak ground …

The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …

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 …

Feature selection is a key pre-processing technique for classification which aims at
removing irrelevant or redundant features from a given dataset. Generally speaking, feature …

In this article, a new feature selection (FS) algorithm, called simple, fast, and efficient (SFE),
is proposed for high-dimensional datasets. The SFE algorithm performs its search process …

Grey Wolf Optimizer (GWO) simulates the grey wolves' nature in leadership and hunting
manners. GWO showed a good performance in the literature as a meta-heuristic algorithm …