Project Development using Artificial Intelligence for Traffic and Transportation
| dc.contributor.advisor | Bérczes, Tamás Márton | |
| dc.contributor.author | Adiyasuren, Oyundelger | |
| dc.contributor.department | DE--Informatikai Kar | |
| dc.date.accessioned | 2026-02-12T18:06:58Z | |
| dc.date.available | 2026-02-12T18:06:58Z | |
| dc.date.created | 2025-11-04 | |
| dc.description.abstract | This thesis explores the development of an AI-driven system for improving traffic and transportation management. It applies machine learning and data analytics methods to predict traffic flow and prevent accidents. The research focuses on building accurate, scalable models that can analyze real-world data and support decision-making in urban mobility. By integrating artificial intelligence techniques with transportation datasets, the study demonstrates how automation and predictive modeling can enhance safety and efficiency. The results contribute to the growing field of intelligent transportation systems and highlight the potential of AI for solving modern traffic challenges. | |
| dc.description.course | Programtervező informatikus | |
| dc.description.degree | BSc/BA | |
| dc.format.extent | 49 | |
| dc.identifier.uri | https://hdl.handle.net/2437/404394 | |
| dc.language.iso | en | |
| dc.rights.info | Hozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében. | |
| dc.subject | Artificial Intelligence , Machine Learning, Accident Prediction, Traffic Prediction | |
| dc.subject.dspace | Informatics | |
| dc.title | Project Development using Artificial Intelligence for Traffic and Transportation | |
| dc.title.translated | Közlekedés és szállítás területén alkalmazott mesterséges intelligenciát használó projektfejlesztés |
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