# DR-RNN: A deep residual recurrent neural network for model reduction

@article{Kani2017DRRNNAD, title={DR-RNN: A deep residual recurrent neural network for model reduction}, author={J. Nagoor Kani and Ahmed H. Elsheikh}, journal={ArXiv}, year={2017}, volume={abs/1709.00939} }

We introduce a deep residual recurrent neural network (DR-RNN) as an efficient model reduction technique for nonlinear dynamical systems. The developed DR-RNN is inspired by the iterative steps of line search methods in finding the residual minimiser of numerically discretized differential equations. We formulate this iterative scheme as stacked recurrent neural network (RNN) embedded with the dynamical structure of the emulated differential equations. Numerical examples demonstrate that DR-RNN… CONTINUE READING

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