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A Modified Grey Wolf Algorithm with Applications to Engineering [PDF]

open access: yesمجله مدل سازی در مهندسی
In this contribution, a modified gray wolf algorithm for use in engineering applications is presented. The grey wolf algorithm is one of the meta-heuristic optimization methods that has recently been widely used by researchers due to its good ...
Vahid Mahboub
doaj   +2 more sources

A Novel Dynamic Generalized Opposition-Based Grey Wolf Optimization Algorithm

open access: yesAlgorithms, 2018
To enhance the convergence speed and calculation precision of the grey wolf optimization algorithm (GWO), this paper proposes a dynamic generalized opposition-based grey wolf optimization algorithm (DOGWO). A dynamic generalized opposition-based learning
Yanzhen Xing, Donghui Wang, Leiou Wang
doaj   +2 more sources

A Grey Wolf Optimization Based Algorithm for Optimum Camera Placement

open access: yesWireless Personal Communications, 2019
Camera placement is very important for surveillance applications. Proposed work presents a new method of optimum placement of visual sensors for maximum coverage of the predefined surveillance space.
Gupta, D., Kaushik, A., Indu, S.
core   +4 more sources

A Modified Grey Wolf Optimizer Based Data Clustering Algorithm

open access: yesApplied Artificial Intelligence, 2021
Data clustering is an important data analysis and data mining tool in many fields such as pattern recognition and image processing. The goal of data clustering is to optimally organize similar objects into clusters.
Peyman Bayat   +2 more
core   +3 more sources

Improved grey wolf optimisation algorithms [PDF]

open access: yesThe Journal of Engineering, 2020
The grey wolf optimisation (GWO) algorithm has fewer numbers of variables and appears quite simple with outstanding capabilities in solving the problems, which are used to describe mathematically what human met in nature. However, it still has its capability to be improved in the convergence ratio, stability, and reduce the errors.
Zheng‐ming Gao   +2 more
openaire   +1 more source

Grey Wolf Optimization Algorithm: A Survey

open access: yesIraqi Journal of Science, 2023
     The Gray Wolf Optimizer (GWO) is a population-based meta-heuristic algorithm  that belongs to the family of swarm intelligence algorithms inspired by the social behavior of gray wolves, in particular the social hierarchy and hunting mechanism. Because of its simplicity, flexibility, and few parameters to be tuned, it has been applied to a wide ...
Mohammed H. Hashem   +2 more
openaire   +1 more source

A new K-means grey wolf algorithm for engineering problems [PDF]

open access: yesWorld Journal of Engineering, 2021
Purpose This paper aims at studying meta-heuristic algorithms. One of the common meta-heuristic optimization algorithms is called grey wolf optimization (GWO). The key aim is to enhance the limitations of the wolves’ searching process of attacking gray wolves. Design/
Mohammed, Hardi M.   +4 more
openaire   +4 more sources

Dynamic characterization of a master–slave robotic manipulator using a hybrid grey wolf–whale optimization algorithm [PDF]

open access: yes, 2021
This article presents a novel hybrid algorithm based on the grey-wolf optimizer and whale optimization algorithm, referred here as grey-wolf optimizer–whale optimization algorithm, for the dynamic parametric modelling of a four degree-of-freedom master ...
Thaha, MA   +3 more
core   +1 more source

Cascaded H-bridge multilevel inverters optimization using adaptive grey wolf optimizer with local search

open access: yes, 2021
With the transformation of transmission and distribution grids into smart grids that are more dominated by renewable energy, power electronics-based inverters that can improve power quality are becoming more visible.
Mirjalili, S, Neshat, M, Ceylan, O
core   +1 more source

Matlab Code of Enhanced Opposition Based Grey Wolf Optimization Algorithm

open access: yes, 2023
Here, the Matlab code of Enhanced Opposition Based Grey Wolf Optimization Algorithm is ...
Mohapatra, P
core   +2 more sources

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