An integrated blade optimization approach based on parallel ANN and GA with hierarchical fair competition dynamic-niche

Zhang, Bin; Wang, Tong; Gu, Changzhan; Xin-wei, Shu

doi:10.1007/s12206-011-0413-0

Cited by 4 publications

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This model was highly consistent to the objective function and could shorten the calculation time by 10 times. Zhang et al 23 proposed a method of GA with hierarchical fair competition dynamic-niche (GA-HFCDN) based on MPL and GA, and optimized the plane cascade and blower blades.…”

Section: Application Of Ai In Aerodynamic Modelsmentioning

confidence: 99%

Application of Artificial Intelligence in Computational Fluid Dynamics

Wang

2021

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

This review discusses the recent application of artificial intelligence (AI) algorithms in five aspects of computational fluid dynamics: aerodynamic models, turbulence models, some specific flows, and mass and heat transfer. Currently, there are three main coupling models. The first is the data-driven model to obtain the input−output relationship without involving any physical mechanisms. The second is the physical model to optimize the existing models by AI algorithms. The third is the hybrid model involving both data and physical mechanisms. Among various AI algorithms, artificial neural network is usually applied to build data-driven models and has been successfully employed in the mentioned five fields. Other AI algorithms such as recursive neural network, support vector machine, and naive Bayes are mainly used for the physical models. Finally, the development tendency of coupling models and how to choose an appropriate model are given in the conclusions and prospects.

show abstract

Section: Application Of Ai In Aerodynamic Modelsmentioning

confidence: 99%