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Multi-task Recurrent Neural Networks to Simultaneously Infer Mode and Purpose in GPS Trajectories
While there's an assumption of higher performance of multi-task over sing-task learners, the results of this study does not hold such an assumption and shows, in the context of mode and trip purpose inference from GPS trajectory data, a multi-task learning approach does not bring any considerable advantage over single-task learners.
Smart Mobility Ontology: Current Trends and Future Directions
Ontology is the explicit and formal representation of the concepts in a domain and relations among them.
Ensemble Convolutional Neural Networks for Mode Inference in Smartphone Travel Survey
In our final model, we combine the output of CNN models using "average voting", "majority voting" and "optimal weights" methods.
Semi-supervised GANs to Infer Travel Modes in GPS Trajectories
Semi-supervised Generative Adversarial Networks (GANs) are developed in the context of travel mode inference with uni-dimensional smartphone trajectory data.
