A noise-immune Kalman filter for short-term traffic flow forecasting-Reference-Cited by-同舟云学术

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A noise-immune Kalman filter for short-term traffic flow forecasting

Published:2019-12 Issue: Volume:536 Page:122601
ISSN:0378-4371
Container-title:Physica A: Statistical Mechanics and its Applications
language:en
Short-container-title:Physica A: Statistical Mechanics and its Applications

Author:

Cai Lingru,Zhang Zhanchang,Yang Junjie,Yu Yidan,Zhou Teng,Qin Jing

Funder

NSFC, China

Natural Science Foundation of Guangdong Province, China

Education Science Planning Project of Guangdong Province, China

STU Scientific Research Foundation for Talents

Science and Technology Planning Project of Guangdong Province, China

Hong Kong Polytechnic University, China

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Statistics and Probability

Reference47 articles.

1. SVRGSA: A hybrid learning based model for short-term traffic flow forecasting;Cai;IET Intell. Transp. Syst.,2019

2. δ-agree AdaBoost stacked autoencoder for short-term traffic flow forecasting;Zhou;Neurocomputing,2017

3. A learning-based multimodel integrated framework for dynamic traffic flow forecasting;Zhou;Neural Process. Lett.,2019

4. Improved multi-variable grey forecasting model with a dynamic background-value coefficient and its application;Zeng;Comput. Ind. Eng.,2018

5. Urban freeway traffic flow prediction: application of seasonal autoregressive integrated moving average and exponential smoothing models;Williams;Transp. Res. Rec.,1998

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