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DeepOKAN: Deep operator network based on Kolmogorov Arnold networks for mechanics problems
Diab W. Abueidda
, Panos Pantidis
, Mostafa E. Mobasher
National Center for Supercomputing Applications (NCSA)
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peer-review
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Keyphrases
Mechanical Problems
100%
Kolmogorov
100%
Network Applications
100%
Deep Operator Network
100%
Neural Network
66%
Prediction Accuracy
66%
Radial Basis Function
66%
Neural Operators
66%
Sinusoidal Wave
33%
Engineering Design
33%
Network Architecture
33%
Approximation Property
33%
Prediction Skill
33%
B-spline
33%
Complex Engineering
33%
Poisson Problem
33%
Neural Network Architecture
33%
Digital Engineering
33%
Scenario Prediction
33%
Orthotropic Elasticity
33%
Design Insight
33%
Training Loss
33%
Conventional Neural Network
33%
DeepONet
33%
Gaussian Radial Basis Function
33%
Engineering
Radial Basis Function
100%
Network Operator
100%
Accurate Prediction
66%
Engineering
33%
Transients
33%
Gaussians
33%
Good Approximation
33%
Input Parameter
33%
Design Engineering
33%
Prediction Capability
33%
Output Field
33%
Neural Network Architecture
33%
Chemical Engineering
Neural Network
100%
Material Science
Elasticity
100%