Jianling Huang

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The new line station passenger flow forecast for urban rail is important in public transport service. The lack of the historical data of new rail line makes the forecast be a challenge. Traditional method always forecast the station passenger flow based on the land use numerical indicators, which is complex and not accurate. This paper proposes a novel(More)
Public transportation automatic fare collection (AFC) systems are able to continuously record large amounts of passenger travel information, providing massive, low-cost data for research on regulations pertaining to public transport. This data can be used not only to analyze characteristics of passengers' trips but also to evaluate transport policies that(More)
The lack of the historical data of new rail line makes the passenger flow distribution prediction be a challenge. Traditional methods always use simple factors, which can not reflect the complexity of OD distribution. This paper proposes a novel passenger flow distribution prediction method based on multi-factor model. This method obtains quantitative(More)
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