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Survey of spatio-temporal sequence prediction methods

Li Weia
Tao Weia
Zhou Xingyub
Pan Zhisonga
a. College of Command & Control Engineering, b. College of Communication Engineering, Army Engineering University of PLA, Nanjing 210007, China

Abstract

With the advancement of data acquisition technology, spatiotemporal data with geographic location information are growing rapidly, so it is urgent to explore effective spatiotemporal data modeling methods. Spatiotemporal sequence prediction is one of the basic methods in spatiotemporal data modeling and widely used in many fields. At present, there is no Chinese literature on its review, so it is of great significance to summarize these methods. For the spatiotemporal sequence prediction problem, this paper reviewed its application background and development history. Then it introduced some related definitions and characteristics. According to its category, the spatiotemporal sequence prediction methods, based on traditional methods, classical machine learning methods and deep learning methods are analyzed respectively as well as their application scope, advantages and disadvantages. Finally, this paper made a review and prospect over the research directions of spatiotemporal sequence prediction, laying a theoretical foundation for researchers to further study this problem.

Foundation Support

国家自然科学基金资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.05.0184
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 10
Section: Survey
Pages: 2881-2888
Serial Number: 1001-3695(2020)10-001-2881-08

Publish History

[2020-10-05] Printed Article

Cite This Article

黎维, 陶蔚, 周星宇, 等. 时空序列预测方法综述 [J]. 计算机应用研究, 2020, 37 (10): 2881-2888. (Li Wei, Tao Wei, Zhou Xingyu, et al. Survey of spatio-temporal sequence prediction methods [J]. Application Research of Computers, 2020, 37 (10): 2881-2888. )

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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