Results 161 to 170 of about 30,520 (198)

Node Collaborative Strategy for 3D Coverage Based on Hopping Adaptive Grey Wolf Optimizer in Wireless Sensor Network. [PDF]

Sensors (Basel)
Wang M, Wu Z, Fan B, Wang Y.
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Multi-criteria decision analysis approach on parametric optimization of abrasive waterjet pocket milling in Ti-6Al-4V alloy. [PDF]

Sci Rep
Naresh Raj KL, Jayavelu S, Kumar MS, Kumar A, Swarna B.   +4 more
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Optimizing hyperparameters of YOLOv10 for arson detection using advanced optimization algorithms. [PDF]

PLoS One
Abbod AA, Abdulmunim ME, Mageed IA.
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GWO: a review and applications

International Journal of System Assurance Engineering and Management, 2020
From the solitudinarian era to the present, the human race has been striving towards the betterment of his life by trying to find out the hidden secrets of our nature. Some time back one would hardly think that colonies of ant, pack of grey wolves, and elephants would be used to design an optimization algorithm.
Ganga Negi, Anuj Kumar, Sangeeta Pant, Mangey Ram   +3 more
openaire   +1 more source

AGWO: Advanced GWO in multi-layer perception optimization

Expert Systems with Applications, 2021
Abstract The Multi-Layer Perceptron (MLP) has been applied into many real-world problems as one of the most extensively used Neural Networks (NNs). It often suffers from local stagnation and premature convergence problems when treating the specific datasets.
Xianqiu Meng, Jianhua Jiang, Huan Wang
openaire   +1 more source

I-GWO and Ex-GWO: improved algorithms of the Grey Wolf Optimizer to solve global optimization problems

Engineering with Computers, 2019
In this paper, two novel meta-heuristic algorithms are introduced to solve global optimization problems inspired by the Grey Wolf Optimizer (GWO) algorithm. In the GWO algorithm, wolves are likely to be located in regions close to each other. Therefore, as they catch the hunt (approaching the solution), they may create an intensity in the same or ...
Amir Seyyedabbasi, Farzad Kiani
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Training LSSVM with GWO for price forecasting

2015 International Conference on Informatics, Electronics & Vision (ICIEV), 2015
This paper presents a hybrid forecasting model namely Grey Wolf Optimizer-Least Squares Support Vector Machines (GWO-LSSVM). In this study, a great deal of attention was paid in determining LSSVM's hyper parameters. For that matter, the GWO is utilized an optimization tool for optimizing the said hyper parameters.
Zuriani Mustaffa, Mohd Herwan Sulaiman, Mohamad Nizam Mohmad Kahar   +2 more
openaire   +1 more source

Grey Wolf Optimization (GWO) Algorithm

2017
This chapter describes the grey wolf optimization (GWO) algorithm as one of the new meta-heuristic algorithms. First, a brief literature review is presented and then the natural process of the GWO algorithm is described. Also, the optimization process and a pseudo code of the GWO algorithm are presented in this chapter.
Hossein Rezaei, Omid Bozorg-Haddad, Xuefeng Chu   +2 more
openaire   +1 more source