International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 1 (January-February 2025) Submit your research before last 3 days of February to publish your research paper in the issue of January-February.

Advancing Traffic volume prediction and Synthetic data generation With machine learning and deep learning

Author(s) Sanika Atul Inamdar, Soham Suhas Kulkarni
Country India
Abstract The difficulty of dealing with traffic jams, pollution, road accidents, and any other disturbances in the management of the city becomes more and more troublesome as the traffic increases. So, adequate traffic management is required. So, our study includes traffic prediction for particular weather using machine learning and deep learning techniques, including Random Forest (RF), Long Short Term Memory (LSTM), AutoEncoders, and Generative Adversarial Networks (GAN). The research highlights the utility of such models in forecasting traffic patterns and creating realistic synthetic data for simulation by analyzing the static and temporal aspects of the traffic data. The results show that these systems enhance traffic management systems and facilitate the development of smarter cities.
Keywords Traffic Volume Prediction, Machine Learning, Random Forest (RF), Long Short-Term Memory (LSTM), Autoencoder, Generative Adversarial Networks (GANs), Sequential Data, Traffic Flow Forecasting, Synthetic Traffic Data, Regression Models, Deep Learning, Urban Traffic Management, Intelligent Transportation Systems (ITS), Model Comparison, Traffic Data Analysis
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-01-20
Cite This Advancing Traffic volume prediction and Synthetic data generation With machine learning and deep learning - Sanika Atul Inamdar, Soham Suhas Kulkarni - IJFMR Volume 7, Issue 1, January-February 2025. DOI 10.36948/ijfmr.2025.v07i01.35530
DOI https://doi.org/10.36948/ijfmr.2025.v07i01.35530
Short DOI https://doi.org/g82gmh

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