Abstract
Artificial neural networks have been used in a variety of prediction models because of their flexibility in modeling complicated systems. Using the automatic passenger counter data collected by New Jersey Transit, a model based on a neural network was developed to predict bus arrival times. Test runs showed that the predicted travel times generated by the models are reasonably close to the actual arrival times.
| Original language | English |
|---|---|
| Pages (from-to) | 267-283 |
| Number of pages | 17 |
| Journal | Journal of Advanced Transportation |
| Volume | 41 |
| Issue number | 3 |
| DOIs | |
| State | Published - 2007 |
ASJC Scopus subject areas
- Automotive Engineering
- Economics and Econometrics
- Mechanical Engineering
- Computer Science Applications
- Strategy and Management
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