Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

Abstract The Sine Cosine Algorithm (SCA) is a population-based optimization algorithm
introduced by Mirjalili in 2016, motivated by the trigonometric sine and cosine functions …

This paper proposes a novel population-based optimization method, called Aquila Optimizer
(AO), which is inspired by the Aquila's behaviors in nature during the process of catching the …

Nature-inspired optimization algorithms can solve different engineering and scientific
problems owing to their easiness and flexibility. There is no need for structural modifications …

The grasshopper optimization algorithm is one of the dominant modern meta-heuristic
optimization algorithms. It has been successfully applied to various optimization problems in …

After the boom and bust of cryptocurrencies' prices in recent years, Bitcoin has been
increasingly regarded as an investment asset. Because of its highly volatile nature, there is a …

Abstract Grey Wolf Optimizer (GWO) is a new swarm intelligence algorithm mimicking the
behaviours of grey wolves. Its abilities include fast convergence, simplicity and easy …

One of the major problems in Big Data is a large number of features or dimensions, which
causes the issue of “the curse of dimensionality” when applying machine learning …

Efficient task scheduling is considered as one of the main critical challenges in cloud
computing. Task scheduling is an NP-complete problem, so finding the best solution is …

This paper completely introduces an exhaustive and a comprehensive review of the so-
called salp swarm algorithm (SSA) and discussions its main characteristics. SSA is one of …