Traffic Flow Prediction using Long Short-Term Memory Network and Optimized Spatial Temporal Dependencies-Reference-Cited by-同舟云学术

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Traffic Flow Prediction using Long Short-Term Memory Network and Optimized Spatial Temporal Dependencies

Published:2021-12-15 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Conference on Big Data (Big Data)
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Author:

Ara Zinat,Hashemi Mahdi

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9671263/9671273/09671381.pdf?arnumber=9671381

Reference32 articles.

1. Long Short-Term Memory

2. Performance Measurement System (PeMS) Data Source,0

3. Traffic flow prediction using lstm with feature enhancement;yang;Neurocomputing,2018

4. A Period-Specific Combined Traffic Flow Prediction Based on Travel Speed Clustering

5. A Comparative Study of Three Multivariate Short-Term Freeway Traffic Flow Forecasting Methods With Missing Data

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1. GRAPHITE — Generative Reasoning and Analysis for Predictive Handling in Traffic Efficiency;Information Fusion;2024-06

2. Closing the Knowledge Gap in Designing Data Annotation Interfaces for AI-powered Disaster Management Analytic Systems;Proceedings of the 29th International Conference on Intelligent User Interfaces;2024-03-18

3. CDSTAEP: Cross-Domain Spatial-Temporal Association Learning for Abnormal Events Prediction;Applied Sciences;2023-03-13

4. Short-Term Traffic Prediction Using Deep Learning Long Short-Term Memory: Taxonomy, Applications, Challenges, and Future Trends;IEEE Access;2023

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