An improved traffic flow forecasting based control logic using parametrical doped learning and truncated dual flow optimization model
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems
Link
https://link.springer.com/content/pdf/10.1007/s11276-022-03020-x.pdf
Reference25 articles.
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2. Omkar, G., & Vasantha Kumar, S. (2017). Time series decomposition model for traffic flow forecasting in urban midblock sections. In: 2017 International conference on smart technologies for smart nation (SmartTechCon). IEEE, 2017.
3. Chen, X., et al. (2017). Spatiotemporal variable and parameter selection using sparse hybrid genetic algorithm for traffic flow forecasting. International Journal of Distributed Sensor Networks, 13(6), 1550147717713376.
4. Guo, L., & Yuan, Y. (2017). Forecast method of short-term passenger flow on urban rail transit. In: Proceedings of the 2017 VI international conference on network, communication and computing. 2017.
5. Milam, R. T., et al. (2017). Closing the induced vehicle travel gap between research and practice. Transportation research record, 2653(1), 10–16.
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1. An adaptive model of optimal traffic flow prediction using adaptive wildfire optimization and spatial pattern super learning;Wireless Networks;2024-02-03
2. Comprehensive Evaluation Method for Traffic Flow Data Quality Based on Grey Correlation Analysis and Particle Swarm Optimization;Journal of Systems Science and Systems Engineering;2023-12-02
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