Wind energy conversionProportional integral controllerThe grey wolf optimizer (GWO) is a new meta-heuristic algorithm inspired from the leadership and prey searching, encircling, and hunting of the grey wolves' community. The GWO algorithm has the advantages of simplicity (less control parameters), ...
This study presents the K-means clustering-based grey wolf optimizer, a new algorithm intended to improve the optimization capabilities of the conventional grey wolf optimizer in order to address the problem of data clustering. The process that groups similar items within a dataset into non-overlappi...
1 简介 The grey wolf optimizer (GWO) is a new meta-heuristic algorithm inspired from the leadership and prey searching, encircling, and hunting of the grey wolves’ community. The GWO algorithm has the advantages of simplicity (less control parameters), flexibility, and globalism. In this paper...
A novel hybrid model of augmented grey wolf optimizer and artificial neural network for predicting shear strength of soildoi:10.1007/s40808-022-01610-4Shear strengthANNHHOGWOAGWOMeta-heuristic algorithmsDue to the critical importance of accurate determination of soil shear strength (SSS) in major ...
The hybrid augmented Lagrangian relaxation鈥搕he grey wolf optimizer technique is recommended to solve the long-term production scheduling problem to improve its performance and, consequently, speed up the convergence. The proposed model has been compared with the results of the hybrid methods gained ...
This document is a correction notice for an article titled "Augmented weighted K-means grey wolf optimizer: An enhanced metaheuristic algorithm for data clustering problems" published in Scientific Reports. The correction addresses an error in the affiliation of two authors, ...