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An improved grey wolf algorithm for global optimization
2018 Chinese Control And Decision Conference (CCDC), 2018This paper presents a novel improved grey wolf optimization (IGWO) to avoid local minimization and premature convergence. In the proposed IGWO algorithm, a nonlinear control parameter based on cosine function is presented to ensure a faster convergence rate of late iteration.
Wendong Gai +3 more
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Fully Informed Grey Wolf Optimizer Algorithm
2020Grey wolf optimizer (GWO) is a newly generated metaheuristic search algorithm inspired by the social behaviour of the grey wolf, which resembles the social structure and hunting mechanism of grey wolves in nature, and is based on three main steps: searching for prey, encircling prey and attacking prey. This paper presents a new variant of GWO algorithm
Priyanka Meiwal +2 more
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An Optimized Grey Wolf Algorithm
2022 IEEE International Conference on Sensing, Diagnostics, Prognostics, and Control ( SDPC), 2022Die Zeng +5 more
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An improved grey wolf optimizer algorithm integrated with Cuckoo Search
2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2017Grey Wolf Optimizer (GWO) is a new meta-heuristic optimization. It is inspired by the unique predator strategy and organization system of grey wolves. Since the GWO algorithm is easy to fall into local optimum especially when it is used in the high-dimensional data, an improved GWO algorithm combined with Cuckoo Search (CS) is proposed in this paper ...
Hui Xu, Xiang Liu, Jun Su
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The defect of the Grey Wolf optimization algorithm and its verification method
Knowledge-Based Systems, 2019Abstract Grey wolf optimization algorithm (GWO) is a new meta-heuristic optimization technology. Its principle is to imitate the behavior of grey wolves in nature to hunt in a cooperative way. GWO is different from others in terms of model structure.
Peifeng Niu +3 more
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Grey wolf optimization algorithm for facial image super-resolution
Applied Intelligence, 2018Face image super-resolution (FSR) algorithms are capable of providing a high-resolution image from an input low-resolution (LR) image. Various FSR algorithms use a set of training examples to reconstruct the input LR image. For the purpose, proper weights need to be calculated for each training image. In general, the least square estimation approach is
Shyam Singh Rajput +2 more
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Grey Wolf Cooperative Positioning Algorithm for UWB Network
Mobile Networks and Applications, 2022Bin Xia +3 more
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Memetic Grey Wolf Optimizer Algorithm for Solving the Cumulative CVRP
International Journal of Autonomous and Adaptive Communications Systems, 2023Yanguang Cai +4 more
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Optimize CNN parameters based on grey wolf algorithm
Proceedings of the 2023 5th International Conference on Internet of Things, Automation and Artificial Intelligence, 2023openaire +2 more sources
Grey Wolf Optimizer Algorithm for Suspension Insulator Designing
2021Dyhia Doufene +3 more
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