Cargando…
Gradient-based grey wolf optimizer with Gaussian walk: Application in modelling and prediction of the COVID-19 pandemic
This research proposes a new type of Grey Wolf optimizer named Gradient-based Grey Wolf Optimizer (GGWO). Using gradient information, we accelerated the convergence of the algorithm that enables us to solve well-known complex benchmark functions optimally for the first time in this field. We also us...
Autores principales: | Khalilpourazari, Soheyl, Hashemi Doulabi, Hossein, Özyüksel Çiftçioğlu, Aybike, Weber, Gerhard-Wilhelm |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997148/ https://www.ncbi.nlm.nih.gov/pubmed/33814731 http://dx.doi.org/10.1016/j.eswa.2021.114920 |
Ejemplares similares
-
Designing a hybrid reinforcement learning based algorithm with application in prediction of the COVID-19 pandemic in Quebec
por: Khalilpourazari, Soheyl, et al.
Publicado: (2021) -
A flexible robust model for blood supply chain network design problem
por: Khalilpourazari, Soheyl, et al.
Publicado: (2022) -
Hybrid Gradient Descent Grey Wolf Optimizer for Optimal Feature Selection
por: Kitonyi, Peter Mule, et al.
Publicado: (2021) -
Grey Wolf Optimization algorithm based on Cauchy-Gaussian mutation and improved search strategy
por: Li, Kewen, et al.
Publicado: (2022) -
Improved Grey Wolf Optimization Algorithm and Application
por: Hou, Yuxiang, et al.
Publicado: (2022)