Results 151 to 160 of about 4,807 (213)

A novel hybrid model for species distribution prediction using neural networks and Grey Wolf Optimizer algorithm. [PDF]

Sci Rep
Zhang HT, Yang TT, Wang WT.
europepmc   +1 more source

S-shaped grey wolf optimizer-based FOX algorithm for feature selection. [PDF]

Heliyon
Feda AK, Adegboye M, Adegboye OR, Agyekum EB, Fendzi Mbasso W, Kamel S.   +5 more
europepmc   +1 more source

A Hybrid Deep Learning and Machine Learning Approach with Mobile-EfficientNet and Grey Wolf Optimizer for Lung and Colon Cancer Histopathology Classification. [PDF]

Cancers (Basel)
Ochoa-Ornelas R, Gudiño-Ochoa A, García-Rodríguez JA.   +2 more
europepmc   +1 more source

A Grey Wolf Optimizer Algorithm for Multi-Objective Cumulative Capacitated Vehicle Routing Problem Considering Operation Time. [PDF]

Biomimetics (Basel)
Huang G, Qi Y, Cai Y, Luo Y, Huang H.
europepmc   +1 more source

Grey Wolf Optimizer with Behavior Considerations and Dimensional Learning in Three-Dimensional Tooth Model Reconstruction. [PDF]

Bioengineering (Basel)
Wongkhuenkaew R, Auephanwiriyakul S, Chaiworawitkul M, Theera-Umpon N, Yeesarapat U.   +4 more
europepmc   +1 more source

Exploring the potential of 5G uplink communication: Synergistic integration of joint power control, user grouping, and multi-learning Grey Wolf Optimizer. [PDF]

Sci Rep
Sikkanan S, Kumar C, Manoharan P, Ravichandran S.   +3 more
europepmc   +1 more source

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Grey wolf optimization with momentum for function optimization

Artificial Life and Robotics, 2021
Grey wolf optimization (GWO) is one of the metaheuristics, which imitates the hierarchy structure and hunting mechanism in nature. In this paper, we propose an algorithm of grey wolf optimization with momentum (GWOM). The momentum has a movement vector of search point from a previous position to a current position.
Takuya Muto, Michiharu Maeda
openaire   +2 more sources

Improved dynamic grey wolf optimizer

Frontiers of Information Technology & Electronic Engineering, 2021
In the standard grey wolf optimizer (GWO), the search wolf must wait to update its current position until the comparison between the other search wolves and the three leader wolves is completed. During this waiting period, the standard GWO is seen as the static GWO.
Xiaoqing Zhang 0013, Yuye Zhang, Zhengfeng Ming   +2 more
openaire   +2 more sources

Grey Wolf Optimizer

2020
GWO algorithm is a swarm or population-based meta-heuristic technique developed based on motivation from the hunting pattern of the Grey Wolves (GW). In this study, the model was implemented using MATLAB 2020. Thirty (30) search agents were considered and the maximum number of iterations was set to 1000.
Ahmed F. Ali, Mohamed A. Tawhid
openaire   +2 more sources

IMPROVEMENT OF WOLF LEADER IN THE GREY WOLF OPTIMIZATION

Konya Journal of Engineering Sciences, 2023
The development of optimization algorithms attracts the attention of many analysts as it has advantages such as increasing performance, revenue, and efficiency in various fields, and reducing cost. Swarm-based optimization algorithms, which are among the meta-heuristic methods, are more commonly preferred because they are generally successful.
Onur İNAN, Mustafa Serter UZER
openaire   +2 more sources