Hybrid modeling and prediction of dynamical systems
Fig 4
Predicting neuron potential x3 in random 3-neuron Hindmarsh-Rose networks.
(a) 3000 samples (or 240 ms) of training data (grey circles) are available from each neuron in the network. From the end of the training data (indicated by dashed black line), we want to accurately predict the next 8 ms of x3 (solid black line). (b) Forecast accuracy in predicting 8 ms of x3 when using parametric (black), nonparametric (blue) and hybrid (red) methods. Results averaged over 200 randomly generated 3-neuron Hindmarsh-Rose network realizations and error bars, shown only for every tenth forecast point, denote standard error. At 80% uncertainty (solid line), the hybrid method outperforms both parametric and nonparametric methods. When considering the parametric method with 50% uncertainty, prediction accuracy between it and the hybrid method is comparable over the first 2 ms.