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西北工业大学 国内
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Fusing deep learning features for parameter identification of a stochastic airfoil system
Jing Feng, Xiaolong Wang, Qi Liu,
Yong Xu
, Jürgen Kurths
数学与统计学院
Xi'an University
Shaanxi Normal University
Northwestern Polytechnical University Xian
Institute of Science Tokyo
Potsdam Institute for Climate Impact Research
Humboldt University of Berlin
Fudan University
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探究 'Fusing deep learning features for parameter identification of a stochastic airfoil system' 的科研主题。它们共同构成独一无二的指纹。
分类
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Engineering
Airfoil
100%
Deep Learning Method
100%
System Parameter
100%
Numerical Study
25%
Joints (Structural Components)
25%
Gaussians
25%
Degree of Freedom
25%
Nonlinearity
25%
Uncertainty Quantification
25%
Extracted Feature
25%
Learning System
25%
Stochastic System
25%
Flow Velocity
25%
Learning Task
25%
Two Degree of Freedom
25%
Nonlinear System
25%
Turbulent Flow
25%
Parameter Estimation
25%
Measurement Data
25%
Structural Stiffness
25%
Learning Approach
25%
Colored Noise
25%
Airfoil Geometry
25%
Parameter Estimate
25%
State Measurement
25%
Compact Representation
25%
Observed State
25%
Chemical Engineering
Deep Learning Method
100%
Learning System
33%
Neural Network
33%
Stochastic System
33%
Nonlinear System
33%