Using a Neural Network to Analyze the Impact of Passenger Activity on Bus Dwell Time and Travel Time
| dc.creator | Chen, Mei | |
| dc.creator | Liu, Xiaobo | |
| dc.date | 2017-04-01T14:04:01Z | |
| dc.date.accessioned | 2026-07-09T09:24:04Z | |
| dc.description | This paper applies neural network modeling approach to analyze the impact of passenger activities on bus dwell time and station-to-station travel time. Data used to develop the model was collected by onboard AVL/APC devices. Sensitivity analyses based on a trained neural network were performed to evaluate the relative significance of each passenger activity variable to variation of dwell time and/or station-to-station travel time. Transit providers can use these methods to identify the causes of schedule deviation and to develop improvement measures that are most effective to transit service. | |
| dc.identifier | doi:10.22004/ag.econ.206774 | |
| dc.identifier | https://ageconsearch.umn.edu/record/206774/files/581-701-1-PB.pdf | |
| dc.identifier | http://ageconsearch.umn.edu/record/206774 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/608616 | |
| dc.language | eng | |
| dc.publisher | ||
| dc.source | http://ageconsearch.umn.edu/record/206774 | |
| dc.title | Using a Neural Network to Analyze the Impact of Passenger Activity on Bus Dwell Time and Travel Time | |
| dc.type | Text |