Results 11 to 20 of about 4,807 (213)
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.
Laith Abualigah +2 more
exaly +3 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
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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
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 +3 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
MBB-MOGWO: Modified Boltzmann-Based Multi-Objective Grey Wolf Optimizer [PDF]
SensorsThe primary objective of multi-objective optimization techniques is to identify optimal solutions within the context of conflicting objective functions.
Jing Liu +3 more
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Neural Computing and Applications, 2022 Swarm-based metaheuristic optimization algorithms have demonstrated outstanding performance on a wide range of optimization problems in both science and industry. Despite their merits, a major limitation of such techniques originates from non-automated parameter tuning and lack of systematic stopping criteria that typically leads to inefficient use of ...
Kazem Meidani +3 more
openaire +3 more sources
IEEE Access, 2021 Conventional fuzzy clustering algorithms present several disadvantages with respect to image segmentation, including a tendency to arrive at local optima and a relatively high sensitivity to noise and initial cluster centers.
Xiangxiao Lei, Honglin Ouyang
doaj +1 more source
Advances in Engineering Software, 2014 This work proposes a new meta-heuristic called Grey Wolf Optimizer (GWO) inspired by grey wolves (Canis lupus). The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy.
Seyedali Mirjalili +2 more
openaire +3 more sources