Increasing Robustness of train diagram using data mining techniques

2014 Fiscal Year Final Research Report

• Project/Area Number: 24510199
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Social systems engineering/Safety system
• Research Institution: Chiba Institute of Technology
• Principal Investigator: TOMII Norio 千葉工業大学, 情報科学部, 教授 (50426029)
• Project Period (FY): 2012-04-01 – 2015-03-31
• Keywords: 鉄道 / 遅延 / データマイニング / 決定木 / 相関ルール

Outline of Final Research Achievements

There are increasing complaints from passengers about the delays of trains during rush hours which very often happen. We have tried to explore effective delay reduction measures by applying data mining techniques to the train traffic record data. We have established an algorithm which finds an origin of delays based on the idea of the association rules and an algorithm which explains relationship between drivers’ behavior and the delay of his train.

Free Research Field

情報工学