| Issue |
MATEC Web Conf.
Volume 309, 2020
2019 International Conference on Computer Science Communication and Network Security (CSCNS2019)
|
|
|---|---|---|
| Article Number | 03024 | |
| Number of page(s) | 7 | |
| Section | Smart Algorithms and Recognition | |
| DOI | https://doi.org/10.1051/matecconf/202030903024 | |
| Published online | 04 March 2020 | |
Time series classification based on arima and adaboost
1 Key Laboratory of Intelligence Computing and Novel Software Technology
2 Tianjin University of Technology, TianJin, China 300384
* Corresponding author: Csr_dsp@sina.com
In this paper, a novel time series classification approach, which using auto regressive integrated moving average model (ARIMA) features and Adaptive Boosting (AdaBoost) classifications. ARIMA is particularly suitable for distinguishing time series signal and Adaboost is suitable for features classification. The simulation results have shown that the algorithm is feasible. And this method is more accurate than many existing method in multiple time series problems.
Key words: Time series classification / ARIMA / AdaBoost
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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