Cargando…
Combining multi-objective genetic algorithm and neural network dynamically for the complex optimization problems in physics
Neural network (NN) has been tentatively combined into multi-objective genetic algorithms (MOGAs) to solve the optimization problems in physics. However, the computationally complex physical evaluations and limited computing resources always cause the unsatisfied size of training set, which further...
Autores principales: | Wang, Peilin, Ye, Kuangkuang, Hao, Xuerui, Wang, Jike |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10279691/ https://www.ncbi.nlm.nih.gov/pubmed/36650211 http://dx.doi.org/10.1038/s41598-023-27478-7 |
Ejemplares similares
-
Multi-objective genetic algorithm for synchrotron radiation beamline optimization
por: Zhang, Junyu, et al.
Publicado: (2023) -
Solving dynamic multi-objective problems with a new prediction-based optimization algorithm
por: Zhang, Qingyang, et al.
Publicado: (2021) -
Genetic algorithm for multi-objective experimental optimization
por: Link, Hannes, et al.
Publicado: (2006) -
A new optimization algorithm to solve multi-objective problems
por: Sharifi, Mohammad Reza, et al.
Publicado: (2021) -
A Multi-Objective Carnivorous Plant Algorithm for Solving Constrained Multi-Objective Optimization Problems
por: Yang, Yufei, et al.
Publicado: (2023)