Paper Abstract and Keywords |
Presentation |
2018-07-02 11:15
An investigation of prediction accuracy of bus delay time influenced by the amount of training data and the variation of outlier detection Tsubasa Yamaguchi, Mansur AS, Tsunenori Mine (Kyushu Univ.) AI2018-4 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Prediction of bus delay is one of crucial research tasks in the intelligent transport systems (ITS) field, and is important not only for a bus operation company, but also passengers, who want to know how many minutes a bus will be concretely delayed to get at a bus stop. In this paper, we propose methods to predict bus delay using bus probe data collected from Nov. 21st to Dec. 20th, 2013 and provided by Nishitetsu Bus company. We used several machine learning methods to build the prediction models. Wediscuss experimental results from the points that how much extents the difference of the amount of training data and the variation of outlier detection methods affect prediction accuracy of predicting bus delay. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
scheduled bus / delay time prediction / probe data / machine learning / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 116, AI2018-4, pp. 15-21, July 2018. |
Paper # |
AI2018-4 |
Date of Issue |
2018-06-25 (AI) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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AI2018-4 |
Conference Information |
Committee |
AI |
Conference Date |
2018-07-02 - 2018-07-02 |
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Paper Information |
Registration To |
AI |
Conference Code |
2018-07-AI |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
An investigation of prediction accuracy of bus delay time influenced by the amount of training data and the variation of outlier detection |
Sub Title (in English) |
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Keyword(1) |
scheduled bus |
Keyword(2) |
delay time prediction |
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probe data |
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machine learning |
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1st Author's Name |
Tsubasa Yamaguchi |
1st Author's Affiliation |
Kyushu University (Kyushu Univ.) |
2nd Author's Name |
Mansur AS |
2nd Author's Affiliation |
Kyushu University (Kyushu Univ.) |
3rd Author's Name |
Tsunenori Mine |
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Kyushu University (Kyushu Univ.) |
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Speaker |
Author-1 |
Date Time |
2018-07-02 11:15:00 |
Presentation Time |
25 minutes |
Registration for |
AI |
Paper # |
AI2018-4 |
Volume (vol) |
vol.118 |
Number (no) |
no.116 |
Page |
pp.15-21 |
#Pages |
7 |
Date of Issue |
2018-06-25 (AI) |
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