Data driven nonlinear dynamical systems identification using multi-step CLDNN
In many cases, the equations that dynamical systems are based on are unknown and hard to model and predict. On the other hand, machine learning algorithms are based on the data of a solution as it evolves and do not need equations. In the era of abundant data, using machine learning technology to di...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2019-08-01
|
| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/1.5100558 |