2022
DOI: 10.1016/j.trip.2022.100552
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A Non-parametric Bayesian Network for multivariate probabilistic modelling of Weigh-in-Motion System Data

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Cited by 10 publications
(10 citation statements)
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“…Further details can be found in [1,9,10]. We added new visualizations, which are only accessible in PyBanshee, recently used in [11].…”
Section: Final Commentsmentioning
confidence: 99%
“…Further details can be found in [1,9,10]. We added new visualizations, which are only accessible in PyBanshee, recently used in [11].…”
Section: Final Commentsmentioning
confidence: 99%
“…In other words, measurements were neglected if the traffic had a velocity lower than 40 [km/h]. This specific WIM data-set was chosen because is used as an input for the model developed by [34] from where the second data-set (VH) is obtained (Fig. 10)…”
Section: Traffic Data and Simulationmentioning
confidence: 99%
“…The second data-set (VH) is the result of a Bayesian Networkbased (BN) model developed by [34]. The data-set is a collection of approximately 300.000 vehicles with their corresponding axle weights and inter-axle distances (that consequently define the number of axles per vehicle) that were randomly generated using the BN model.…”
Section: Traffic Data and Simulationmentioning
confidence: 99%
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“…At present, most of the weighing scales in the domestic market are made by adding a fence to the bench scale, which not only restricts the action of the goats but also requires manual counting and recording of ear tags and weight information, which is inefficient due to the amount of required manual labor; this can also be inaccurate. Dynamic scales squeeze the goats into a small space so that they cannot move for the measurements, which is more efficient but can be slow and costly to maintain [4][5][6]. Both of these methods can frighten the goats, lowering their immunity and increasing the incidence of disease, which is not conducive to healthy goat growth.…”
Section: Introductionmentioning
confidence: 99%