A Study of Deep Learning for Network Traffic Data Forecasting

Benedikt Pfülb, Christoph Hardegen, Alexander Gepperth, Sebastian Rieger. A Study of Deep Learning for Network Traffic Data Forecasting. In Igor V. Tetko, Vera Kurková, Pavel Karpov, Fabian J. Theis, editors, Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, Part IV. Volume 11730 of Lecture Notes in Computer Science, pages 497-512, Springer, 2019. [doi]

@inproceedings{PfulbHGR19,
  title = {A Study of Deep Learning for Network Traffic Data Forecasting},
  author = {Benedikt Pfülb and Christoph Hardegen and Alexander Gepperth and Sebastian Rieger},
  year = {2019},
  doi = {10.1007/978-3-030-30490-4_40},
  url = {https://doi.org/10.1007/978-3-030-30490-4_40},
  researchr = {https://researchr.org/publication/PfulbHGR19},
  cites = {0},
  citedby = {0},
  pages = {497-512},
  booktitle = {Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, Part IV},
  editor = {Igor V. Tetko and Vera Kurková and Pavel Karpov and Fabian J. Theis},
  volume = {11730},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-030-30490-4},
}