Open Source Tools for Machine Learning with Big Data in Smart Cities-Reference-Cited by-同舟云学术

Open Source Tools for Machine Learning with Big Data in Smart Cities

Published:2019-05-21 Issue: Volume: Page:153-168
ISSN:2522-8595
Container-title:Smart Cities Performability, Cognition, & Security
language:
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Author:

Ulusar Umit Deniz,Ozcan Deniz Gul,Al-Turjman Fadi

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-14718-1_8

Reference23 articles.

1. Haughton, G., Hunter, C., & Hunter, C. (2004). Sustainable cities. London: Routledge.

2. Seetha, H., Murty, M. N., & Tripathy, B. K. (2001). Modern technologies for big data classification and clustering. Hershey, PA: IGI Global.

3. Zhou, L., Pan, S., Wang, J., & Vasilakos, A. V. (2017, May). Machine learning on big data: Opportunities and challenges. Neurocomputing, 237, 350–361.

4. Ulusar, U. D., Celik, G., Turk, E., Al-Turjman, F., & Guvenc, H. (2019). Practical performability assessment for ZigBee-based sensors in the IoT era. In F. Al-Turjman (Ed.), Performability in internet of things (pp. 21–31). Cham: Springer.

5. Ulusar, U. D., Celik, G., & Al-Turjman, F. (2017). Wireless communication aspects in the internet of things: An overview. In 2017 IEEE 42nd Conference on Local Computer Networks Workshops (LCN Workshops) (pp. 165–169).

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