Detection of Statistically Significant Bus Delay Aggregation by Spatial-Temporal Scanning
| Autor: | Xia Wu, Jyrki Nummenmaa, Tinghai Pang, Lei Duan |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
050210 logistics & transportation
Service quality Service (systems architecture) business.industry Computer science 05 social sciences 03 medical and health sciences 0302 clinical medicine Empirical research Traffic system 0502 economics and business 030212 general & internal medicine business Statistical hypothesis testing Computer network |
| Zdroj: | Web Technologies and Applications ISBN: 9783319458342 APWeb Workshops |
| DOI: | 10.1007/978-3-319-45835-9_24 |
| Popis: | Public bus service plays an indispensable role in modern urban traffic system. With the bus running data, the detection of the statistically significant aggregations of bus delay is useful for optimizing the bus timetable, so that the service quality can be improved. However, previous studies have not considered how to detect bus delay aggregation using statistical hypothesis testing. To fill that gap, this paper considers the detection of bus delay aggregation from bus running data. We present RSTV-Miner, a mining method using statistical hypothesis testing, for detecting statistically significant bus delay aggregation. Our empirical study on real data demonstrates that RSTV-Miner is effective and efficient. |
| Databáze: | OpenAIRE |
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