Prediction of Airfoil Lift Coefficient Based on Multilayer Perceptron
Authors:
- 24 June 2024
- journal article
- research article
- Published by Springer Nature in International Journal of Aeronautical and Space Sciences
- Vol. 26 (1) , 13-20
Abstract
No abstract availableKeywords
Funding Information
- Scientific Research Project of Department of Education of Hunan Province (21C1577)
This publication has 35 references indexed in Scilit:
- Low-Reynolds-number airfoil design optimization using deep-learning-based tailored airfoil modesAerospace Science and Technology, 2022
- Data-enhanced dynamic flight simulations for flight performance analysisAerospace Science and Technology, 2022
- Deep learning based multistage method for inverse design of supercritical airfoilAerospace Science and Technology, 2021
- Rapid airfoil design optimization via neural networks-based parameterization and surrogate modelingAerospace Science and Technology, 2021
- A new soft computing model for daily streamflow forecastingStochastic Environmental Research and Risk Assessment, 2021
- On deep-learning-based geometric filtering in aerodynamic shape optimizationAerospace Science and Technology, 2021
- Fast pressure distribution prediction of airfoils using deep learningAerospace Science and Technology, 2020
- Deep reinforcement learning in fluid mechanics: A promising method for both active flow control and shape optimizationJournal of Hydrodynamics, 2020
- An Improved Deep Convolutional Neural Network to Predict Airfoil Lift Coefficient2020
- Large-Scale Machine Learning with Stochastic Gradient Descent2010