Predicting Transportation Modes of GPS Trajectories Using Feature Engineering and Noise Removal

Author:

Etemad MohammadORCID,Soares Júnior AmílcarORCID,Matwin StanORCID

Publisher

Springer International Publishing

Reference11 articles.

1. Dabiri, S., Heaslip, K.: Inferring transportation modes from GPS trajectories using a convolutional neural network. Transp. Res. Part C Emerg. Technol. 86, 360–371 (2018)

2. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);Y Endo,2016

3. Han, J., Pei, J., Kamber, M.: Data Mining: Concepts and Techniques. Elsevier, Amsterdam (2011)

4. Jiang, X., Souza, E.N., Pesaranghader, A., Hu, B., Silver, D.L., Matwin, S.: trajectorynet: an embedded GPS trajectory representation for point-based classification using recurrent neural networks. arXiv preprint arXiv:1705.02636 (2017)

5. Soares Júnior, A., Moreno, B.N., Times, V.C., Matwin, S., dos Anjos Formiga Cabral, L.: GRASP-UTS: an algorithm for unsupervised trajectory segmentation. Int. J. Geogr. Inf. Sci. 29(1), 46–68 (2015)

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