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Traffic Prediction
Traffic prediction is a task involving the forecasting of traffic conditions, such as vehicle flow and travel time, in specific areas or on roads. As an important application of time series analysis, its core objective is to optimize transportation systems through historical data and real-time information, reduce traffic congestion, improve road usage efficiency, and enhance safety.
METR-LA
TITAN
PeMS07
STAEformer
PEMS-BAY
STD-MAE
PeMS08
PDFormer
PeMSD8
Hierarchical-Attention-LSTM (HierAttnLSTM)
PeMSD4
STD-MAE
PeMS04
PDFormer
PeMSD7
STG-NCDE
EXPY-TKY
STD-MAE
PeMSD7(M)
STD-MAE
NE-BJ
RGDAN
PeMSD7(L)
STD-MAE
LargeST
PatchSTG
PeMSD3
SZ-Taxi
BJTaxi
ST-SSL
NYCTaxi
PeMS-M
NYCBike1
NYCBike2
PeMSD4 (10 days' training data, 60min)
PeMSD4 (10 days' training data, 15min)
DASTNet
PeMSD8 (10 days' training data, 15min)
Beijing Traffic
MemDA
PeMSD7 (10 days' training data, 15min)
HZME(inflow)
PeMSD7 (10 days' training data, 60min)
PeMSD7 (10 days' training data, 30min)
PeMSD8 (10 days' training data, 60min)
Q-Traffic
hybrid Seq2Seq
HZME(outflow)
CorrSTN
PeMSD8 (10 days' training data, 30min)
PeMSD4 (10 days' training data, 30min)