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Hybrid Intelligent Nonlinear Optimization for FDA-MIMO Passive Microwave Arrays Radar on Static Platforms. [PDF]
Micromachines (Basel)Zhang Y, Li W, Yang B, Zhu C, Dong K.
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Gray wolf optimization of photonics crossing waveguides
Nanoengineering: Fabrication, Properties, Optics, Thin Films, and Devices XVIII, 2021In this paper, the Gray Wolf (GWO) algorithm has been used to design and to optimize the geometrical parameters of broadband compact silicon on insulator waveguide crossing structure operating in the wavelength range of 1400–1600 nm. The electromagnetic numerical simulations of the waveguide crossing have been conducted by using an efficient frequency ...
Luana da França Vieira +2 more
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An Optimal Demand Response Strategy Using Gray Wolf Optimization
2021Demand response (DR) keeps up a significant contribution to the growth of electricity generation with transmission and distribution in the phase of advanced grid automation. For future smart grid, basically, two types of demand side management (DSM) strategies have been used with many shiftable or controllable loads.
Ankit Kumar Sharma +3 more
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System Reliability Optimization Using Gray Wolf Optimizer Algorithm
Quality and Reliability Engineering International, 2016For the past two decades, nature‐inspired optimization algorithms have gained enormous popularity among the researchers. On the other hand, complex system reliability optimization problems, which are nonlinear programming problems in nature, are proved to be non‐deterministic polynomial‐time hard (NP‐hard) from a computational point of view.
Anuj Kumar, Sangeeta Pant, Mangey Ram
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Gray Wolf Optimizer for hyperspectral band selection
Applied Soft Computing, 2016Graphical abstractDisplay Omitted HighlightsWe propose a new approach for feature selection in hyperspectral image classification.The problem of band selection is reformulated as a combinatorial problem.We design a new objective function which takes into account two term, the classification error rate and the class separability distance.To optimize the
S.A. Medjahed +3 more
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Design optimization of orbital angular momentum fibers using the gray wolf optimizer
Applied Optics, 2020Optical data communication based on the orbital angular momentum (OAM) of light is a recently proposed method to enhance the transmission capacity of optical fibers. This requires a new type of optical fiber, the main part of the optical communication system, to be designed. Typically, these fibers have a ring-shaped refractive index profile. We aim to
Seyed Mohammad Mirjalili +3 more
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Load balancing in cloud using improved gray wolf optimizer
Concurrency and Computation: Practice and Experience, 2022AbstractCloud computing allocates virtual resources dynamically on user's demand. The sudden rise of data storage and computation in the cloud computing environment may cause an imbalanced workload distribution. As a result, job completion time will be higher in overloaded servers than the underloaded servers in the same environment.
Bhavesh N. Gohil, Dhiren R. Patel
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Clustering Big Datasets Using Orthogonal Gray Wolf Optimizer
2019 International Conference on Information Technology (ICIT), 2019Grey wolf optimization (GWO) is one of the many nature-inspired algorithms that is popular for solving labyrinthine optimization problems. The algorithm uses properties of hunting mechanism and leadership hierarchy of Grey wolves. This manuscript proposes a new variant of GWO called as Orthogonal Grey Wolf Optimization (OGWO).
Satyasai Jagannath Nanda +2 more
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Short-Term Hydrothermal Scheduling Using Gray Wolf Optimization
2020In this paper, a new nature-inspired meta-heuristic called gray wolf optimization (GWO), is implemented for solution of short-term hydrothermal scheduling (STHTS) problems. The analytical model of GWO is based on the rigors social hierarchy and hunting procedure of gray wolves by their unique three steps: searching for prey, encircling of prey, and ...
Khushboo Sharma +2 more
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Feature Subset Selection Approach by Gray-Wolf Optimization
2015Feature selection algorithm explores the data to eliminate noisy, irrelevant, redundant data, and simultaneously optimize the classification performance. In this paper, a classification accuracy-based fitness function is proposed by gray-wolf optimizer to find optimal feature subset. Gray-wolf optimizer is a new evolutionary computation technique which
E. Emary +3 more
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