Mining Train Delays by Using Frequent Itemsets
D. Kishore Babu1, Y. Nagasatish2, P. M. Prasuna3
1D. Kishore Babu, Asst. Professor, Dept. of CSE, BVCITS Amalapuram, E.G. Dist, A.P., India.
2Y. Nagasatish, Asst. Professor, Dept. of CSE, BVCITS Amalapuram, E.G. Dist, A.P., India.
3P. M. Prasuna, Professor, Dept. of CSE, BVCITS Amalapuram, E.G. Dist, A.P., India.
Manuscript received on December 07, 2011. | Revised Manuscript received on December 23, 2011. | Manuscript published on January 05, 2012. | PP: 318-323 | Volume-1 Issue-6, January 2012. | Retrieval Number: F0335121611/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Indian railway network has a high traffic density with Vijayawada a s its gravity c e n t e r . The s t a r -shape of the network implies heavily loaded bifurcations in which knock-on delays are likely to occur. Knock-on d ela ys should b e minimized to improve th e total punctuality in the network. Based o n experience, t h e most critical junctions in the traffic flow are known, but others might be hidden. To reveal the hidden patterns of trains passing d e l a y s t o e a c h o t h e r, we study, adapt and apply the state-of-the-art techniques for mining frequent episodes to this specific problem.
Keywords: Train delays, Data Analysis, Pattern mining, frequent itemsets, Hidden trains.