Mr. Bo Su Profile

Bo Su

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 7 December 2023 Paper

A method for traffic network speed forecasting based on GCN-BiLSTM

Wei Zhang, Bo Su, Pan Yang, Yiling Hu

Proceedings Volume 12941, 129414H (2023) https://doi.org/10.1117/12.3011491

KEYWORDS: Roads, Data modeling, Matrices, Deep learning, Convolutional neural networks, Machine learning, Feature extraction, Data acquisition, Statistical modeling

Read Abstract +

Accurate prediction results in the field of intelligent transportation systems are crucial. They enable commuters to make informed decisions regarding travel modes, routes, and departure times, which can significantly enhance travel efficiency. Due to the unique characteristics of road networks, accurate prediction is particularly important. This paper proposes a deep learning method combining graph convolutional neural network and bidirectional long short-term memory network. The model uses GCN to extract the topological structure features of the road network, learns the spatial correlation of the road, and uses BiLSTM to learn the temporal correlation of the road network speed data. Finally, non-traffic factors are integrated into the deep model to improve the accuracy of prediction. It is verified by real road network speed data. Experimental results show that compared with the traditional prediction model, the root mean square error of the GCN-BiLSTM combination model is 1.455, the mean absolute error is 1.283, the R2 of the coefficient of determination is 0.937, and the 95% confidence interval is [-2.866, 3.233], which are better than other models. The proposed model has higher accuracy and stability.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years