A study on knowledge acquisition from a large-scale traffic data set by using structured data mining techniques
| Project/Area Number |
23760469
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Civil engineering project/Traffic engineering
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| Research Institution | Muroran Institute of Technology |
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Principal Investigator |
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| Research Collaborator |
HASEGAWA Hironobu 秋田工業高等専門学校, 環境都市工学科, 助教 (00533374)
MATSUDA Masanori (株)ドーコン交通事業本部, 交通部, 主任技師 (70629857)
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| Project Period (FY) |
2011 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2012: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2011: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | データマイニング / 大規模交通データセット / ソフトコンピューティング / 交通行動分析 |
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| Research Abstract |
The aims of this study are to apply the structure data mining techniques for large-scale traffic data recorded by an information and communication system to obtain information to contribute to a transportation planning and to build analysis technique to extract a characteristic movement pattern automatically. In this study, we tried to apply various data mining techniques for the person trip data which were the statistics data described the movement of the person in the city and log data of community cycle (bicycle sharing system in an urban area) which was the new transportation mode in the city. As a result, the extraction of the knowledge to modify the estimate of a characteristic movement pattern to be in large-scale data set, the construction of a highly precise transportation choice model, the whole traffic phenomenon such as the change in the traffic pattern at the daily traffic and the non-daily traffic was enabled.
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Report
(3 results)
Research Products
(14 results)
