Results 31 to 40 of about 4,354 (214)

Diversity-Based Evolutionary Population Dynamics: A New Operator for Grey Wolf Optimizer

, 2022
Evolutionary Population Dynamics (EPD) refers to eliminating poor individuals in nature, which is the opposite of survival of the fittest. Although this method can improve the median of the whole population of the meta-heuristic algorithms, it suffers ...
Safavi, HR, Mirjalili, S, Mohamed Abd Elaziz, Hamid R. Safavi, Seyedali Mirjalili, Rezaei, F, Farshad Rezaei, Amir H. Gandomi, Gandomi, AH, Abualigah, L, Laith Abualigah, Abd Elaziz, M   +11 more
core   +1 more source

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

Elektronika 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

A New Enhanced Hybrid Grey Wolf Optimizer (GWO) Combined with Elephant Herding Optimization (EHO) Algorithm for Engineering Optimization

Journal of Soft Computing in Civil Engineering, 2022
Although the exploitation of GWO advances sharply, it has limitations for continuous implementing exploration. On the other hand, the EHO algorithm easily has shown its capability to prevent local optima. For hybridization and by considering the advantages of GWO and the abilities of EHO, it would be impressive to combine these two algorithms.
Hoseini, Zaynab, Varaee, Hesam, Rafieizonooz, Mahdi, Jay Kim, JangHo   +3 more
openaire   +2 more sources

An Improved Grey Wolf Optimizer and Its Application in Robot Path Planning

Biomimetics, 2023
This paper discusses a hybrid grey wolf optimizer utilizing a clone selection algorithm (pGWO-CSA) to overcome the disadvantages of a standard grey wolf optimizer (GWO), such as slow convergence speed, low accuracy in the single-peak function, and easily
Yun Ou, Pengfei Yin, Liping Mo
doaj   +1 more source

Grey wolf optimizer: Theory, literature review, and application in computational fluid dynamics problems

, 2020
This chapter first discusses inspirations, methematicam models, and an in-depth literature of the recently proposed Grey Wolf Optimizer (GWO). Then, several experiments are conducted to analyze and benchmark the performance of different variants and ...
Mirjalili, S, Heidari, AA, Faris, H, Aljarah, I, Mafarja, M   +4 more
core   +1 more source

A novel version of grey wolf optimizer based on a balance function and its application for hyperparameters optimization in deep neural network (DNN) for structural damage identification

, 2022
In this paper, a new method has been proposed to optimize the hyper parameters in Deep neural network (DNN). For this purpose, a new version of Grey Wolf Optimizer named New Balance Grey Wolf Optimizer (NB-GWO) is successfully developed for the first ...
Mirjalili, S, Abdel Wahab, M, Thanh Cuong-Le, Cuong-Le, T, Sang-To, T, Thanh Sang-To, Seyedali Mirjalili, Minh, HL, Samir Khatir, Khatir, S, Hoang-Le Minh, Magd Abdel Wahab   +11 more
core   +1 more source

WEIGHTED GREY WOLF OPTIMIZER WITH IMPROVED CONVERGENCE RATE IN TRAINING MULTI-LAYER PERCEPTRON TO SOLVE CLASSIFICATION PROBLEMS

Jordanian Journal of Computers and Information Technology, 2021
The Grey Wolf Optimizer (GWO) is a very recently developed and emerging swarm-intelligent algorithm. The GWO algorithm was inspired by the social dominance hierarchy and hunting strategy of the grey wolves that has been successfully tailored to tackle ...
Alok Kumar, Lekhraj, Anoj Kumar
doaj   +1 more source

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

International 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, INAN, Onur, AKTO, İhtisam   +2 more
openaire   +3 more sources

GWO-LPWSN: Grey Wolf Optimization Algorithm for Node Localization Problem in Wireless Sensor Networks [PDF]

Journal of Computer Networks and Communications, 2017
Seyedali Mirjalili et al. (2014) introduced a completely unique metaheuristic technique particularly grey wolf optimization (GWO). This algorithm mimics the social behavior of grey wolves whereas it follows the leadership hierarchy and attacking strategy. The rising issue in wireless sensor network (WSN) is localization problem.
Rajakumar Ramalingam, Jayavel Amudhavel, P. Dhavachelvan, T. Vengattaraman   +3 more
openaire   +2 more sources

Optimization of Thermal Efficiency and Unburned Carbon in Fly Ash of Coal-Fired Utility Boiler via Grey Wolf Optimizer Algorithm

IEEE Access, 2019
This paper focuses on improving thermal efficiency and reducing unburned carbon in fly ash by optimizing operating parameters via a novel high-efficient swarm intelligence optimization algorithm (grey wolf optimizer algorithm, GWO) for coal-fired boiler.
Yiding Zhao, Qinghe Wu, Heng Li, Shuhua Ma, Ping He, Jun Zhao, Yangmin Li   +6 more
doaj   +1 more source