DeepTrend: A Deep Hierarchical Neural Network for Traffic Flow Prediction

Understand

In this paper, we consider the temporal pattern in traffic flow time series, and implement a deep learning model for traffic flow prediction.

• Detrending based methods decompose original flow series into trend and residual series, in which trend describes the fixed temporal pattern in traffic flow and residual series is used for prediction.
• Inspired by the detrending method, we propose DeepTrend, a deep hierarchical neural network used for traffic flow prediction which considers and extracts the time-variant trend.
• DeepTrend has two stacked layers: extraction layer and prediction layer.