Metaheuristics are popularly used in various fields, and they have attracted much attention
in the scientific and industrial communities. In recent years, the number of new metaheuristic …

Abstract Machine learning (ML) has been extensively applied to model geohazards, yielding
tremendous success. However, researchers and practitioners still face challenges in …

This paper presents a novel nature-inspired optimization paradigm, named as squirrel
search algorithm (SSA). This optimizer imitates the dynamic foraging behaviour of southern …

The behavior of natural phenomena has become one of the most popular sources for
researchers to design optimization algorithms for scientific, computing and engineering …

This paper introduces a novel reference tracking control approach implemented using a
combination of the Actor-Critic Reinforcement Learning (RL) framework and the Grey Wolf …

One of the most crucial aspects of image segmentation is multilevel thresholding. However,
multilevel thresholding becomes increasingly more computationally complex as the number …

Abstract The Firefly Algorithm (FA) is a highly efficient population-based optimization
technique developed by mimicking the flashing behavior of fireflies when mating. This article …

In this article, an improved variant of the grey wolf optimizer (GWO) named gaze cues
learning-based grey wolf optimizer (GGWO) is proposed. The main intentions are to reduce …

Abstract Background: The Chimp Optimization Algorithm (ChOA) is a hunting-based model
and can be utilized as a set of optimization rules to tackle optimization problems. Due to …

Advancements in medical technology have created numerous large datasets including
many features. Usually, all captured features are not necessary, and there are redundant …