This study develops a novel metaheuristic algorithm that is motivated by the behavior of
jellyfish in the ocean and is called artificial Jellyfish Search (JS) optimizer. The simulation of …

Grey wolf optimizer (GWO) is a widespread metaphor-based algorithm based on the
enhanced variants of velocity-free particle swarm optimizer with proven defects and …

Quickly, accurately and reliably extract the parameters of solar photovoltaic (PV) model is
very critical to simulate, evaluate and control the PV systems. During the past few years …

This paper proposed an improved Grey Wolf Optimizer (GWO) to resolve the problem of
instability and convergence accuracy when GWO is used as a meta-heuristic algorithm with …

Abstract Grey Wolf Optimizer (GWO) is a new nature-inspired metaheuristic algorithm based
on the leadership and social behaviour of grey wolves in nature. It has shown potential to …

This study developed a novel optimization algorithm, called Forensic-Based Investigation
(FBI), inspired by the suspect investigation–location–pursuit process that is used by police …

In this research, we propose an enhanced Grey Wolf Optimizer (GWO) for designing the
evolving Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) networks for …

Grey wolf optimizer (GWO) is a new nature-inspired algorithm that simulates the predatory
behaviors of grey wolves in nature. The GWO mainly divides the whole hunting process into …

The process of dimensionality reduction is a crucial solution to deal with the dimensionality
problem that may be faced when dealing with the majority of machine learning techniques …

The optimization of truss structures is a complex computing problem with many local minima,
while metaheuristics are naturally suited to deal with multimodal problems without the need …