An integrated approach implementing sliding window and DTW distance for time series forecasting tasks-Reference-Cited by-同舟云学术

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An integrated approach implementing sliding window and DTW distance for time series forecasting tasks

Published:2023-04-18 Issue:17 Volume:53 Page:20614-20625
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Tao Zhifu,Xu Qinghua,Liu Xi,Liu Jinpei

Funder

Humanities and Social Sciences Research Youth Project of the Ministry of Education of China

Natural Science Foundation of Anhui Province

National Natural Science Foundation of China

The teacher project of Anhui Ecology and Economic Development Research Center in 2021

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-023-04590-9.pdf

Reference36 articles.

1. Bates JM, Granger CWJ (1969) The combination of forecasts. J Oper Res Soc 20(4):451–468

2. Clemen RT (1989) Combining forecasts: a review and annotated bibliography. Int J Forecast 5 (4):559–583

3. Oliveira RD, Assis TD, Firmino P, Ferreira T (2017) Copulas-based time series combined forecasters. Inf Sci 376:110–124

4. Fastrich B, Winker P (2014) Combining forecasts with missing data: making use of portfolio theory. Comput Econ 44:127–152

5. Jiang A, Chi Q, Gao J et al (2019) An integrated approach to forecasting intermittent demand for electric power materials. Comput Econ 53:1309–1335

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