A framework based on sparse representation model for time series prediction in smart city

doi:10.1007/s11704-019-8395-7

Front. Comput. Sci.

2021, Vol. 15

Issue (1) : 151305 https://doi.org/10.1007/s11704-019-8395-7

RESEARCH ARTICLE

A framework based on sparse representation model for time series prediction in smart city

Zhiyong YU¹, Xiangping ZHENG¹, Fangwan HUANG¹(

), Wenzhong GUO¹, Lin SUN², Zhiwen YU³

¹. College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China
². Hangzhou Key Laboratory for IoT Technology & Application, Zhejiang University City College, Hangzhou 310015, China
³. School of Computer Science, Northwestern Polytechnical University, Xi’an 710072, China

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Abstract

Smart city driven by Big Data and Internet of Things (IoT) has become a most promising trend of the future. As one important function of smart city, event alert based on time series prediction is faced with the challenge of how to extract and represent discriminative features of sensing knowledge from the massive sequential data generated by IoT devices. In this paper, a framework based on sparse representation model (SRM) for time series prediction is proposed as an efficient approach to tackle this challenge. After dividing the over-complete dictionary into upper and lower parts, the main idea of SRMis to obtain the sparse representation of time series based on the upper part firstly, and then realize the prediction of future values based on the lower part. The choice of different dictionaries has a significant impact on the performance of SRM. This paper focuses on the study of dictionary construction strategy and summarizes eight variants of SRM. Experimental results demonstrate that SRM can deal with different types of time series prediction flexibly and effectively.

Keywords sparse representation smart city time series prediction dictionary construction

Corresponding Author(s): Fangwan HUANG

Just Accepted Date: 16 October 2019 Issue Date: 24 September 2020

Cite this article:

Zhiyong YU,Xiangping ZHENG,Fangwan HUANG, et al. A framework based on sparse representation model for time series prediction in smart city[J]. Front. Comput. Sci., 2021, 15(1): 151305.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-019-8395-7
https://academic.hep.com.cn/fcs/EN/Y2021/V15/I1/151305

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