May 29, 2019 · Overall, this paper can help transit agencies to better understand the deterministic and stochastic changes of the passenger flow, and implement ...
Based on smart card data, Li et al. [4] proposed a multiscale radial basis function network to predict irregular alighting ridership before a special event, ...
Oct 22, 2024 · Overall, this paper can help transit agencies to better understand the deterministic and stochastic changes of the passenger flow, and implement ...
In this paper, besides traditional smart card data, we incorporate social media data into passenger flow prediction.
Pereira et al. (2015) developed a neural network algorithm to predict public transit arrivals for special events using social media and smart card data, as well ...
Three empirical studies with special events in Beijing demonstrate that the proposed algorithm can effectively predict the emergence of passenger flow bursts.
Forecasting short-term subway passenger flow under special ...
ui.adsabs.harvard.edu › abs › abstract
A multiscale radial basis function (MSRBF) network is proposed.MSRBF network can predict irregular subway passenger flow under special events.
Combined with transit smart card data, this approach not only exhibits superior predictive performance over prevailing computational intelligence methods for ...
Jan 7, 2022 · First, arrival passenger count (APC) is predicted based on SARIMA; then, departure passenger count (DPC) is predicted based on event algorithm, ...
The daily average daily passenger flow during the morning peak period reached 1.25 million passengers / day, and the average daily passenger flow during the ...
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