… a traffic prediction procedure intended for application to traffic engineering … -term (non-periodical
or temporal) and longer-term (hour or day) variations. We directly predict the longer-term …

… For instance, we can consider learning a traffic prediction function using the data of a
metropolitan city A, and then apply the learnt prediction function to another metropolitan city B. …

… ABSTRACT Recently, traffic prediction based on deep … -wide links and long-term traffic
prediction for next few hours. To … network-wide and longterm traffic prediction. STANN captures …

… approaches, especially at the boundaries of rush hours and at the beginning of unexpected
traffic events, and for long term prediction. The rest of this paper is organized as follows: …

… long term prediction deviate from the “zero line” more seriously than those for short term
prediction… still superior to other models in long-term traffic speed prediction in terms of MAPE and …

… The main contributions of this paper are, • We proposed a novel end-to-end framework for
traffic prediction, which can model spatial, short-term and longterm periodical dependencies …

… in the long-term horizon (eg, 1 hour ahead). We argue that the long-term traffic prediction
is … time to take actions to optimize the traffic according to the prediction. We also use the T-Test …

… to perform long-term forecasting than short-term forecasting … prediction capacity for long-term
traffic flow, this paper proposes a novel approach for long-term traffic flow prediction with …

… long-term traffic time is a challenging task. In long-term traffic prediction problem, the future
traffic time not only depends on the current traffic situation but also has some relationship with …

… is proposed to learn the long-term periodic dependency. The proposed mechanism captures
both longterm periodic information and temporal shifting in traffic sequence via attention …