Ensembles of neural networks for forecasting of time series of spacecraft telemetry

Abstract

We analyzed different approaches to developing ensembles of neural networks in respect to their forecasting accuracy. We describe a two level model of ensembles of neural networks for forecasting of telemetry time series of spacecraft’s subsystems. A possibility of additional training of these ensembles of neural networks is examined. Our results show that use of ensembles of neural networks with dynamic weighing allows us to reduce the forecasting error.