A Distance Correlation-Based Approach to Characterize the Effectiveness of Recurrent Neural Networks for Time Series Forecasting

arXiv:2307.15830v2 Announce Type: replace
Abstract: Time series forecasting has received a lot of attention, with recurrent neural networks (RNNs) being one of the widely used models due to their ability to handle sequential data. Previous studies on RNN time series forecasting, however, show inconsistent outcomes and offer few explanations for performance variations among the datasets. In this paper, we provide an approach to link time series characteristics with RNN components via the versatile metric of distance correlation. This metric allows …

abstract arxiv attention correlation cs.lg data forecasting however networks neural networks recurrent neural networks rnn series show studies time series time series forecasting type