Results 31 to 40 of about 8,834 (223)

A novel hybrid GWO-SCA approach for optimization problems

open access: yesEngineering Science and Technology, an International Journal, 2017
Recent trend of research is to hybridize two and several number of variants to find out better quality of solution of practical and recent real applications in the field of global optimization problems.
N. Singh, S.B. Singh
doaj   +1 more source

Power system operation enhancement using a new hybrid methodology for optimal allocation of FACTS devices

open access: yesEnergy Reports, 2022
The proposed research article introduces a new hybrid heuristic algorithm based on Autonomous Groups Particle Swarm and Grey Wolf optimizers (AGPSO-GWO) via multi-objective function for the allocation of the Flexible Alternating Current Transmission ...
Ahmed A. Shehata   +3 more
doaj   +1 more source

Enhanced Grey Wolf Optimizer Based MPPT Algorithm of PV System Under Partial Shaded Condition [PDF]

open access: yes, 2017
Partial shading condition is one of the adverse phenomena which effects the power output of photovoltaic (PV) systems due to inaccurate tracking of global maximum power point.
Cherukuri, S. K. (Santhan)   +1 more
core   +1 more source

Path Planning For A Mobile Robot Using The Chessboard Method And Gray Wolf Optimization Algorithm In Static And Dynamic Environments [PDF]

open access: yesمدیریت مهندسی و رایانش نرم
The Grey Wolf Optimization (GWO) algorithm, a computational optimization method inspired by the social behavior of wolves, has recently been effectively used to solve optimization and routing problems.
Ali Hatami Zadeh   +2 more
doaj   +1 more source

Multi-Area Load Frequency Control of Hydro-Thermal-Wind Power Based on Improved Grey Wolf Optimization Algorithm

open access: yesElektronika ir Elektrotechnika, 2020
The mathematical model of load frequency control is established in the interconnected power system of hydro, thermal, and wind for solving the problem of frequency instability in this paper. Besides, the improved grey wolf optimization algorithm (GWO) is
Fannie Kong, Jinfang Li, Daliang Yang
doaj   +1 more source

Grey Wolf Optimizer and Discrete Chaotic Map for Substitution Boxes Design and Optimization

open access: yesIEEE Access, 2023
A metaheuristic approach based on the nature-inspired and well-known Grey Wolf Optimization algorithm (GWO) was employed in this study to design an approach for retrieving strong designs of $8\times 8$ substitution boxes (S-boxes).
Ali Ibrahim Lawah   +4 more
doaj   +1 more source

Optimization algorithms for steady state analysis of self excited induction generator [PDF]

open access: yes, 2023
The current publication is directed to evaluate the steady state performance of three-phase self-excited induction generator (SEIG) utilizing particle swarm optimization (PSO), grey wolf optimization (GWO), wale optimization algorithm (WOA), genetic ...
Anagreh, Aysha   +2 more
core   +2 more sources

A beamforming study of the linear antenna array using grey wolf optimization algorithm [PDF]

open access: yes, 2020
The grey wolf optimization (GWO) algorithm is considered an inspired meta-heuristic algorithm, which inspired by the social hierarchy and hunting behavior of the grey wolves.
Hasan Sallomi, Adheed   +2 more
core   +3 more sources

A New Galactic Swarm Optimization Algorithm Enhanced with Grey Wolf Optimizer for Training Artificial Neural Networks [PDF]

open access: yes, 2021
This paper proposes a new Galactic Swarm Optimization (GSO) algorithm enhanced with Grey Wolf Optimizer (GWO).The proposed algorithm is used to train a feedforward Neural Network for function approximation.
Geraldine Bessie Amali.D, Mahammed Mohsina, Umadevi K S
core   +2 more sources

Grey Wolf Optimizer (GWO) Algorithm to Solve the Partitional Clustering Problem

open access: yesInternational Journal of Intelligent Systems and Applications in Engineering, 2019
The clustering which is an unsupervised classification method is very important for data processing applications. The main purpose of the clustering is to separate the data samples into different groups by using the similarity (or dissimilarity) between data samples. There are many conventional and heuristic algorithms which are used for the clustering
KARAKOYUN, Murat   +2 more
openaire   +3 more sources

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