Results 121 to 130 of about 13,304 (184)

Exploring the potential of 5G uplink communication: Synergistic integration of joint power control, user grouping, and multi-learning Grey Wolf Optimizer. [PDF]

Sci Rep
Sikkanan S, Kumar C, Manoharan P, Ravichandran S.   +3 more
europepmc   +1 more source

Different type of pay later facility for green product with selling price dependent demand using grey wolf optimizer. [PDF]

Heliyon
Alrasheedi AF.
europepmc   +1 more source

Improvised grey wolf optimizer assisted artificial neural network (IGWO-ANN) predictive models to accurately predict the permeate flux of desalination plants. [PDF]

Heliyon
Mahadeva R, Kumar M, Diwan A, Manik G, Dixit S, Das G, Gupta V, Sharma A.   +7 more
europepmc   +1 more source

Novel grey wolf optimizer based parameters selection for GARCH and ARIMA models for stock price prediction. [PDF]

PeerJ Comput Sci
Bagalkot SS, A DH, Naik N.
europepmc   +1 more source

Author Correction: Augmented weighted K-means grey wolf optimizer: An enhanced metaheuristic algorithm for data clustering problems. [PDF]

Sci Rep
Premkumar M, Sinha G, Ramasamy MD, Sahu S, Subramanyam CB, Sowmya R, Abualigah L, Derebew B.   +7 more
europepmc   +1 more source

Chaotic opposition learning with mirror reflection and worst individual disturbance grey wolf optimizer for continuous global numerical optimization. [PDF]

Sci Rep
Adegboye OR, Feda AK, Ojekemi OS, Agyekum EB, Hussien AG, Kamel S.   +5 more
europepmc   +1 more source

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Improved dynamic grey wolf optimizer

Frontiers of Information Technology & Electronic Engineering, 2021
In the standard grey wolf optimizer (GWO), the search wolf must wait to update its current position until the comparison between the other search wolves and the three leader wolves is completed. During this waiting period, the standard GWO is seen as the static GWO.
Xiaoqing Zhang, Yuye Zhang, Zhengfeng Ming   +2 more
openaire   +1 more source

Swarmed Grey Wolf Optimizer

The Chinese Journal of Artificial Intelligence, 2022
Background: The Particle Swarm Optimization (PSO) algorithm is amongst the utmost favourable optimization algorithms often employed in hybrid procedures by the researchers considering simplicity, smaller count of parameters involved, convergence speed and capability of searching global optima.
Sumita Gulati, Ashok Pal
openaire   +1 more source

Grey Wolf Optimizer

2020
GWO algorithm is a swarm or population-based meta-heuristic technique developed based on motivation from the hunting pattern of the Grey Wolves (GW). In this study, the model was implemented using MATLAB 2020. Thirty (30) search agents were considered and the maximum number of iterations was set to 1000.
Ahmed F. Ali, Mohamed A. Tawhid
openaire   +2 more sources