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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. We present in this paper the Volitive Grey Wolf Optimizer (VGWO), a Grey Wolf Optimizer variant created by the addition of the collective ...
Joao Paulo Silva +4 more
semanticscholar +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
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A Novel Hybrid Algorithm Based on Grey Wolf Optimizer and Fireworks Algorithm
Sensors, 2020 Grey wolf optimizer (GWO) is a meta-heuristic algorithm inspired by the hierarchy of grey wolves (Canis lupus). Fireworks algorithm (FWA) is a nature-inspired optimization method mimicking the explosion process of fireworks for optimization problems ...
Zhihang Yue, Sen Zhang, Wendong Xiao
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Grey wolf optimizer: a review of recent variants and applications
Neural computing & applications (Print), 2017 Grey wolf optimizer (GWO) is one of recent metaheuristics swarm intelligence methods. It has been widely tailored for a wide variety of optimization problems due to its impressive characteristics over other swarm intelligence methods: it has very few ...
Hossam Faris +3 more
semanticscholar +2 more sources
Recent Advances in Grey Wolf Optimizer, its Versions and Applications: Review
IEEE Access, 2023 The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm intelligence methods, drawing inspiration from the hunting behavior of wolf packs.
S. Makhadmeh +6 more
semanticscholar +2 more sources
Jurnal Ilmiah Teknik Industri, 2022 Energy consumption has become a significant issue in businesses. It is known that the industrial sector has consumed nearly half of the world's total energy consumption in some cases.
Cynthia Novel Al-Imron +2 more
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Image Denoising with Modified Grey Wolf Optimizer
Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2018 In this study, image denoising hasbeen realized with with the one of the recent Nature-Inspired optimizationalgorithms, Grey Wolf Optimizer(GWO). GWO is one of the recent most studiedcontinous optimization algorithm which performs better than the ...
Pakize Erdoğmuş, Hüseyin Avni Ardaç
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Selective Opposition based Grey Wolf Optimization
Expert Systems with Applications, 2020 Abstract The use of metaheuristics is widespread for optimization in both scientific and industrial problems due to several reasons, including flexibility, simplicity, and robustness. Grey Wolf Optimizer (GWO) is one of the most recent and popular algorithms in this area.
Souvik Dhargupta +3 more
openaire +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
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Journal of Applied Mathematics, 2017 A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO).
Narinder Singh, S. B. Singh
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