Augmented weighted K-means grey wolf optimizer: An enhanced metaheuristic algorithm for data clustering problems [PDF]
Scientific ReportsThis study presents the K-means clustering-based grey wolf optimizer, a new algorithm intended to improve the optimization capabilities of the conventional grey wolf optimizer in order to address the problem of data clustering.
Dr M Premkumar +2 more
exaly +3 more sources
A novel algorithm of MGWO-based PI controller for a single-stage grid-connected flyback inverter with ZVS [PDF]
Automatika, 2022 An effective approach on zero-voltage switching scheme for a single-stage grid-connected flyback inverter along with the introduction of Modified Grey Wolf Optimizer technique based on the proportional integral controller is proposed.
N. K. Sakthivel, S. Sutha
doaj +3 more sources
A multi hidden recurrent neural network with a modified grey wolf optimizer.
PLoS ONE, 2019 Identifying university students' weaknesses results in better learning and can function as an early warning system to enable students to improve. However, the satisfaction level of existing systems is not promising.
Tarik A Rashid +2 more
doaj +2 more sources
A hybrid algorithm of grey wolf optimizer and harris hawks optimization for solving global optimization problems with improved convergence performance [PDF]
Scientific Reports, 2023 The grey wolf optimizer is an effective and well-known meta-heuristic algorithm, but it also has the weaknesses of insufficient population diversity, falling into local optimal solutions easily, and unsatisfactory convergence speed. Therefore, we propose
Binbin Tu +3 more
doaj +2 more sources
CMGWO: Grey wolf optimizer for fusion cell-like P systems [PDF]
HeliyonThe grey wolf optimizer is a widely used parametric optimization algorithm. It is affected by the structure and rank of grey wolves and is prone to falling into the local optimum.
Yourui Huang +4 more
doaj +2 more sources
A novel fault diagnosis method for gearbox based on RVMD and TELM with composite chaotic grey wolf optimizer [PDF]
Scientific ReportsFault diagnosis for gearbox by robust variational mode decomposition (RVMD) and twin extreme learning machine (TELM) with composite chaotic grey wolf optimizer (CCGWO) is proposed in this study. Robust variational mode decomposition is an advanced signal
Xuebin Huang +3 more
doaj +2 more sources
Volitive Grey Wolf Optimizer [PDF]
Anais do XVI Congresso Brasileiro de Inteligência Computacional, 2023 Swarm-based metaheuristics have become the most prominent method for solving optimization problems. Several operators already proposed in the literature can also be reused to expand the current metaheuristics.
Bastos Filho, Carmelo +4 more
core +2 more sources
Improved Alpha-Guided Grey Wolf Optimizer [PDF]
IEEE Access, 2019 Grey wolf optimizer (GWO) is a new meta-heuristic swarm intelligence algorithm, which has shown promising performance in solving optimization problems. In order to improve the convergence speed of GWO, an alpha-guided GWO (AgGWO), in which the evolving ...
Pin Hu +4 more
doaj +2 more sources
Grey wolf optimizer with self-repulsion strategy for feature selection [PDF]
Scientific ReportsFeature selection is one of the most critical steps in big data analysis. Accurately extracting correct features from massive data can effectively improve the accuracy of big data processing algorithms.
Yufeng Wang +5 more
doaj +2 more sources
An integrative TLBO-driven hybrid grey wolf optimizer for the efficient resolution of multi-dimensional, nonlinear engineering problems [PDF]
Scientific ReportsThis research article introduces a hybrid optimization algorithm, referred to as Grey Wolf Optimizer-Teaching Learning Based Optimization (GWO-TLBO), which extends the Grey Wolf Optimizer (GWO) by integrating it with Teaching-Learning-Based Optimization (
Harleenpal Singh +6 more
doaj +2 more sources