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Deep Learning on Traffic State Prediction
STRIDE Webinar

Robert W. Whalin, Ph.D., Jackson State University
Guojing Hu, Ph.D., Jackson State University

Short-term traffic flow data are often corrupted by local noise, which may reduce the accuracy and effectiveness of prediction models. Aiming at such issue, this research developed a hybrid approach that combines denoising schemes with a deep learning model to improve the accuracy of short-term traffic flow forecasting. Experimental results demonstrated that the proposed hybrid model outperforms other considered counterparts in both accuracy and efficiency.

Nov 3, 2022 12:00 PM in Eastern Time (US and Canada)

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