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Can I read Deep-learning Based Discovery of Partial Differential Equations in Integral Form from Sparse and Noisy Data on EtoBox?
Deep-learning Based Discovery of Partial Differential Equations in Integral Form from Sparse and Noisy Data by Hao Xu; Dongxiao Zhang; Nanzhe Wang is a Engineering article available to read on EtoBox.
What is Deep-learning Based Discovery of Partial Differential Equations in Integral Form from Sparse and Noisy Data about?
A deep-learning framework is developed to discover PDE in integral form. • The proposed method performs well for PDEs with high-order derivatives. • The proposed method can handle heterogeneous parametric PDEs. • The proposed method is robust to noise and sparse data. • The utilization of integral form increases the accuracy of PDE discovery.
Who reads Deep-learning Based Discovery of Partial Differential Equations in Integral Form from Sparse and Noisy Data?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Hao Xu; Dongxiao Zhang; Nanzhe Wang
- Publisher
- Elsevier BV
- Published
- 2021
- Language
- EN
- Field
- Engineering (Physical Sciences)