Using supervised learning methods to predict the stop duration of heavy vehicles.
In this thesis project, we attempt to predict the stop duration of heavy vehicles using data based on GPS positions collected in a previous project. All of the training and prediction is done in AWS SageMaker, and we explore possibilities with Linear Learner, K-Nearest Neighbors and XGBoost, all of...
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| Format: | Others |
| Language: | English |
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Mälardalens högskola, Akademin för utbildning, kultur och kommunikation
2020
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-50977 |
