Artificial intelligence based commuter behaviour profiling framework using Internet of things for real-time decision-making-Reference-Cited by-同舟云学术

Artificial intelligence based commuter behaviour profiling framework using Internet of things for real-time decision-making

Published:2020-02-20 Issue:20 Volume:32 Page:16057-16071
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Bandaragoda Tharindu,Adikari Achini,Nawaratne Rashmika,Nallaperuma Dinithi,Luhach Ashish Kr.,Kempitiya Thimal,Nguyen Su,Alahakoon Damminda,De Silva Daswin,Chilamkurti Naveen^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/s00521-020-04736-7.pdf

Reference40 articles.

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2. Taylor MA, Bonsall PW (2017) Understanding traffic systems: data analysis and presentation. Routledge, London

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4. Wemegah TD, Zhu S (2017) Big data challenges in transportation: a case study of traffic volume count from massive Radio Frequency Identification(RFID) data. In: 2017 international conference on the frontiers and advances in data science (FADS), pp 58–63. https://doi.org/10.1109/fads.2017.8253194

5. Schimbinschi F, Nguyen XV, Bailey J, Leckie C, Vu H, Kotagiri R (2015) Traffic forecasting in complex urban networks: leveraging big data and machine learning. In: 2015 IEEE international conference on big data (big data), 2015, pp 1019–1024. https://doi.org/10.1109/bigdata.2015.7363854

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