Predicting IoT-based Traffic in Smart Cities using Neural Networks

Yanghua Wang

Bakalářská práce

Abstract:

Congested road networks are negatively impacting the sustainability of many cities due to worsening air contamination. In this Study, Neural Networks with Deep Learning Are used Traffic in Smart Cities. I used a data Set Called Traffic, Which Was Collected by Sensors Placement at Four Intersects, and then the time server situations are produced based on the GRU model, which is thoroughly investigated using different settings.

Abstract:

Congested road networks are negatively impacting the sustainability of many cities due to worsening air contamination. In this Study, Neural Networks with Deep Learning Are used Traffic in Smart Cities. I used a data Set Called Traffic, Which Was Collected by Sensors Placement at Four Intersects, and then the time server situations are produced based on the GRU model, which is thoroughly investigated using different settings.

Keywords

smart transportation, smart city, internet of things, machine learning, neural networks

Jazyk práce: angličtina

Datum vytvoření / odevzdání či podání práce: 30. 6. 2023

Zveřejnit od: 31. 12. 2999

Obhajoba závěrečné práce

• Vedoucí: prof. Ing. Petr Hájek, Ph.D.

Univerzita Pardubice

Fakulta ekonomicko-správní

Bakalářský studijní program / obor:
Informatics and System Engineering / Informatics in Public Administration