Source Estimation for Propagation Processes on Complex Networks with an Application to Delays in Public Transportation Systems
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About this item
| Description: |
Manitz, J (Georg-August-Universität Göttingen, Boston University)
Friday 26th August 2016 - 11:30 to 12:10 |
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| Created: | 2016-08-31 17:22 |
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| Collection: | Theoretical Foundations for Statistical Network Analysis |
| Publisher: | Isaac Newton Institute |
| Copyright: | Manitz, J |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
|
| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | Co-authors: Jonas Harbering (University of Göttingen), Marie Schmidt (Erasmus University Rotterdam), Thomas Kneib (University of Göttingen), Anita Schöbel (University of Göttingen)
The correct identification of the source of a propagation process is crucial in many research fields. As a specific application, we onsider source estimation of delays in public transportation networks. We propose two approaches: a effective distance median and a backtracking method. The former is based on the structurally generic effective distance-based approach for the identification of infectious disease origins, and the latter is specifically designed for delay propagation. We examine the performance of both methods in simulation studies and in an application to the German railway system, and compare the results to a centrality-based approach for source detection. |
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