dc.contributor.author |
Fernando, J.L.P.K. |
|
dc.contributor.author |
De Silva, M.D.S. |
|
dc.contributor.author |
Bulathsinhala, B.A.I. |
|
dc.contributor.author |
Wijayasekara, S.K. |
|
dc.date.accessioned |
2021-10-04T08:00:24Z |
|
dc.date.available |
2021-10-04T08:00:24Z |
|
dc.date.issued |
2021-07-27 |
|
dc.identifier.citation |
1st International Conference on Science and Technology, Faculty of Technology,27th July 2021. South Eastern University of Sri Lanka, University Park, Oluvil, Sri Lanka. pp. 203-208 |
en_US |
dc.identifier.isbn |
978-624-5736-17-1 |
|
dc.identifier.uri |
http://ir.lib.seu.ac.lk/handle/123456789/5765 |
|
dc.description.abstract |
The current railway system in Sri Lanka ,there are 1687 Railway Level Crossings Systems
(RLC) with three types of RLCs protection methods namely RLCs with barriers, RLC with
bell and light, and unprotected RLCs. As per our observation, we identified that there is no decision criterion on identifying the most suitable RLC protection mode for different RLC environments in the current railway system and this leads to an increase in the collision rate of the road traffic and the train schedule. Therefore, as a solution in this work, an accurate prediction method is introduced based on the 'Regression Tree Analysis' method to identify the most appropriate component out of barriers or bell and light in a specific RLC. |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
Faculty of Technology, South Eastern University of Sri Lanka, Sri Lanka |
en_US |
dc.relation.ispartofseries |
International Conference on Science and Technology,; |
|
dc.subject |
Train Vehicle Unit, |
en_US |
dc.subject |
Regression tree analysis, |
en_US |
dc.subject |
Machine learning, |
en_US |
dc.subject |
Level crossing |
en_US |
dc.subject |
RLC, |
en_US |
dc.subject |
Accidents |
en_US |
dc.title |
An Optimized algorithm to select the most appropriate gate type for a given level crossing in Sri Lanka |
en_US |
dc.type |
Article |
en_US |