A Universal Framework of Spatiotemporal Bias Block for Long-Term Traffic Forecasting

McGill University, Dec. 2019 ~ Feb. 2020
Advisor: Prof. Lijun Sun
Co-worker: Fuqiang Liu, Jiawei Wang, Jingbo Tian and Prof. Luis Miranda-Moreno
Publication: IEEE Transactions on Intelligent Transportation System
Resources: I-TIS DOI

• Introduced a general framework with Bias Block to improve the performance of seq2seq extreme long-time prediction.
• Used STGCN, DCRNN and GWNet as base model and chose Matrix Factorization, VAR and SVR as the baseline to prove that our model obtain higher accuracy and stronger interpretability.
• Geodata visualization with Python and paper writing.