Kasper M. Van Zuilekom

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Transportation engineers are commonly faced with the question of how to extract information from expensive and scarce field data. Modeling the distribution of trips between zones is complex and dependent on the quality and availability of field data. This research explores the performance of neural networks in trip distribution modeling and compares the(More)
SUMMARY The aim of this study is to explore the performances of neural networks in both trip generation and trip distribution modelling and to compare the results with more commonly used models, respectively regression models and doubly constrained gravity models. Trip generation and trip distribution are complex and highly dependent on the quality and(More)
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