Classification and prediction of port variables using Bayesian Networks

Beatriz Molina Serrano, Nicoleta González-Cancelas, Francisco Soler-Flores and Alberto Camarero-Orive

Transport Policy, 2018, vol. 67, issue C, 57-66

Abstract: Many variables are included in planning and management of port terminals. They can be economic, social, environmental and institutional. Agent needs to know relationship between these variables to modify planning conditions. Use of Bayesian Networks allows for classifying, predicting and diagnosing these variables. Bayesian Networks allow for estimating subsequent probability of unknown variables, basing on know variables.

Date: 2018
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DOI: 10.1016/j.tranpol.2017.07.013

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