Bus_arrival_prediction

Project on using ML to implement bus arrival time prediction
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Predicting Transportation Modes Of Gps Trajectories24
4 years agoapache-2.0Python
Understanding transportation mode from GPS (Global Positioning System) traces is an essential topic in the data mobility domain. In this paper, a framework is proposed to predict transportation modes. This framework follows a sequence of five steps: (i) data preparation, where GPS points are grouped in trajectory samples; (ii) point features generation; (iii) trajectory features extraction; (iv) noise removal; (v) normalization. We show that the extraction of the new point features: bearing rate, the rate of rate of change of the bearing rate and the global and local trajectory features, like medians and percentiles enables many classifiers to achieve high accuracy (96.5%) and f1 (96.3%) scores. We also show that the noise removal task affects the performance of all the models tested. Finally, the empirical tests where we compare this work against state-of-art transportation mode prediction strategies show that our framework is competitive and outperforms most of them.
Us Transportationmode24
3 years agomitPython
Transportation Mode Detection with Unconstrained Smartphones Sensors
Trenova15
2 months ago9otherPython
An AI-driven comprehensive suite of applications tailored for the transportation and logistics sector.
Bus_arrival_prediction6
7 years ago1mitPython
Project on using ML to implement bus arrival time prediction
Data6
a year ago
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Python
Machine Learning
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