PofoliaShared via Pofolia

· 2016

Using LSTM and GRU neural network methods for traffic flow prediction

Rui Fu, Zuo‐Feng Zhang, Li Li

Short summary

This paper demonstrates that Recurrent Neural Network (RNN) based deep learning models, specifically LSTM and GRU, outperform traditional ARIMA models for short-term traffic flow prediction.

AI-generated from the title and abstract; the full text is not read.

TakeawaysIn the app
Key pointsIn the app
Ask the paperIn the app

The rest is in the Pofolia app

Takeaways, key points and questions to the paper; new summaries every day for your field. Free.

Sign in on the web to open

Field: Building and Construction

Building and ConstructionEngineering