A spatiotemporal correlative k-nearest neighbor model for short-term traffic multistep forecasting-Reference-Cited by-同舟云学术

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A spatiotemporal correlative k-nearest neighbor model for short-term traffic multistep forecasting

Published:2016-01 Issue: Volume:62 Page:21-34
ISSN:0968-090X
Container-title:Transportation Research Part C: Emerging Technologies
language:en
Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Cai Pinlong,Wang Yunpeng,Lu Guangquan,Chen Peng,Ding Chuan,Sun Jianping

Funder

National Basic Research Program of China

Publisher

Elsevier BV

Subject

Computer Science Applications,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference34 articles.

1. Forecasting of short-term traffic-flow based on improved neurofuzzy models via emotional temporal difference learning algorithm;Abdi;Eng. Appl. Artif. Intell.,2012

2. Short-term traffic flow forecasting of road network based on Elman neural network;Dong;J. Transport. Syst. Eng. Inform. Technol.,2010

3. Intelligent transportation systems—enabling technologies;García-Ortiz;Math. Comput. Modell.,1995

4. Adaptive Kalman filter approach for stochastic short-term traffic flow rate prediction and uncertainty quantification;Guo;Transport. Res. Part C: Emerg. Technol.,2014

5. Non-parametric regression for space–time forecasting under missing data;Haworth;Comput. Environ. Urban Syst.,2012

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