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A physics-informed deep learning paradigm for car-following..:
Mo, Zhaobin
;
Shi, Rongye
;
Di, Xuan
Transportation Research Part C: Emerging Technologies. 130 (2021) - p. 103240 , 2021
Link:
https://doi.org/10.1016/j.trc.2021.103240
RT Journal T1 <Title>A physics-informed deep learning paradigm for car-following models</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.trc.2021.103240&Exemplar=1&LAN=DE A1 Mo, Zhaobin A1 Shi, Rongye A1 Di, Xuan PB Elsevier BV YR 2021 SN 0968-090X JF Transportation Research Part C: Emerging Technologies VO 130 SP 103240 LK http://dx.doi.org/https://doi.org/10.1016/j.trc.2021.103240 DO https://doi.org/10.1016/j.trc.2021.103240 SF ELIB - SuUB Bremen
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