Results 181 to 190 of about 17,774 (232)
Training LSSVM with GWO for price forecasting [PDF]
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 +2 more
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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 +2 more
exaly +4 more sources
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 +2 more
exaly +4 more sources
A novel hybrid PSO–GWO algorithm for optimization problems
Engineering With Computers, 2018In this study, we propose a new hybrid algorithm fusing the exploitation ability of the particle swarm optimization (PSO) with the exploration ability of the grey wolf optimizer (GWO). Our approach combines two methods by replacing a particle of the PSO with small possibility by a particle partially improved with the GWO. We have evaluated our approach
Fatih Ahmet Senel +2 more
exaly +4 more sources
As we celebrate the 30th anniversary of Gender, Work and Organization (GWO), we are excited to welcome our readers to a new chapter of the journal. With a new leadership team of three Editors-in-Chief at the helm, we are poised to build upon the strong foundation laid by a line of distinguished scholars who have served as Editors-in-Chief, each leaving
Wood, Bronwyn +2 more
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GWO: a review and applications
International Journal of System Assurance Engineering and Management, 2020From 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 +3 more
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An Efficient Routing Algorithm for IoT Using GWO Approach
International Journal of Applied Metaheuristic Computing, 2021The internet of things (IoT) is a technology representing a rapidly ubiquitous development. The technologies supporting the IoT are becoming significant as it forms the basic need to analyze the environment and making it smarter. So far, the internet in context of IPs is considered as the largest network globally.
Sharad Sharma, Aparna Kapoor
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Development of geosteering system based on GWO–SVM model
Neural Computing and Applications, 2021Two geological steering models, the particle swarm support vector machine (PSO-SVM) and the gray wolf support vector machine (GWO–SVM), were analyzed to determine the models’ optimal global parameters. The fitness function was used to compare and analyze the models, while the original data and feature reconstruction data were used to simulate and ...
Min Mao +4 more
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AGWO: Advanced GWO in multi-layer perception optimization
Expert Systems with Applications, 2021Abstract 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
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Grey Wolf Optimization (GWO) Algorithm
2017This 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 +2 more
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A hybrid clustering algorithm based on improved GWO and KHM clustering
Journal of Intelligent & Fuzzy Systems, 2022To solve the problem that the K-means algorithm is sensitive to the initial clustering centers and easily falls into local optima, we propose a new hybrid clustering algorithm called the IGWOKHM algorithm. In this paper, we first propose an improved strategy based on a nonlinear convergence factor, an inertial step size, and a dynamic weight to improve
Feng Xue +4 more
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