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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 3
817-821

Outlier-identified Kalman filter for short-term traffic flow forecasting

Bai Weihua1
Zhang Chuanbin1
Zhang Shuangyi2
Zhou Teng2
1. School of Computer Science & Software, School of Big Data, Zhaoqing University, Zhaoqing Guangdong 526061, China
2. Dept. of Computer Science, Shantou University, Shantou Guangdong 515063, China
DOI: 10.19734/j.issn.1001-3695.2020.03.0070

Abstract

This paper presented a novel and effective technique for short-term traffic flow forecasting. The main contribution was an extension of Kalman filter, such that it became to be able to identify the outlier and then filter out it, which was named as outlier-identified Kalman filter. It used the classic Kalman filter to filter out the fluctuations of the traffic flow which led the system uncertainty, and the subtle clues indicating the sudden change of the traffic flow might lose in this operation. To achieve better forecasting accuracy, it used discrete wavelet transform to process the original signal and preserved the useful signals while de-noising. In addition, it applied historical reference values to correct predicted values. Extensive experiments on four benchmark datasets demonstrate an average improvement of 2.919% in MAPE and 79.58 in RMSE.

Foundation Support

国家自然科学基金资助项目(61902232)
广东省自然科学基金资助项目(2018A030313291)
广东省教育科学规划项目(2018GXJK048,2019KTSCX199)
广东大学生科技创新培育专项资金资助项目(pdjh2020b0222)
肇庆市科技专项资金项目(2020G1004)
肇庆学院校级科研项目(2019012612,zlgc201933)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.03.0070
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 3
Section: System Development & Application
Pages: 817-821
Serial Number: 1001-3695(2021)03-034-0817-05

Publish History

[2021-03-05] Printed Article

Cite This Article

白伟华, 张传斌, 张塽旖, 等. 基于异常值识别卡尔曼滤波器的短期交通流预测 [J]. 计算机应用研究, 2021, 38 (3): 817-821. (Bai Weihua, Zhang Chuanbin, Zhang Shuangyi, et al. Outlier-identified Kalman filter for short-term traffic flow forecasting [J]. Application Research of Computers, 2021, 38 (3): 817-821. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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