Original paper

A Bayesian network model to predict the effects of interruptions on train operations

Volume: 114, Pages: 338 - 358
Published: May 1, 2020
Abstract
Based on the Bayesian network (BN) paradigm, we propose a hybrid model to predict the three main consequences of disruptions and disturbances during train operations, namely, the primary delay (L), the number of affected trains (N), and the total delay times (T). To obtain an effective BN structure, we first analyze the dependencies of the involved factors on each station and among adjacent stations, given domain knowledge and expertise about...
Paper Details
Title
A Bayesian network model to predict the effects of interruptions on train operations
Published Date
May 1, 2020
Volume
114
Pages
338 - 358
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