Forecasting across time series databases using recurrent neural networks on groups of similar series: A clustering approach

This work presents a prediction model that can be used with different types of RNN models on subgroups of similar time series, which are identified by time series clustering techniques and consistently outperforms the baseline LSTM model and outperforms all other methods on the CIF2016 forecasting competition dataset.