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International Journal of Production Research Volume 61, 2023 - Issue 3
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Research Articles

Improving forecasting by subsampling seasonal time series

Xixi Lia Department of Mathematics, The University of Manchester, Manchester, UKORCID Iconhttps://orcid.org/0000-0001-5846-3460View further author information
ORCID Icon,
Fotios Petropoulosb School of Management, University of Bath, Bath, UKORCID Iconhttps://orcid.org/0000-0003-3039-4955View further author information
ORCID Icon &
Yanfei Kangc School of Economics and Management, Beihang University, Beijing , People's Republic of ChinaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-8769-6650View further author information
ORCID Icon
Pages 976-992 | Received 04 Jan 2021, Accepted 14 Dec 2021, Published online: 17 Jan 2022

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Read on this site (3)

Fernanda Strozzi & Rossella Pozzi. (2024) Trend and seasonality features extraction with pre-trained CNN and recurrence plot. International Journal of Production Research 62:9, pages 3251-3262.
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Li Li, Yanfei Kang, Fotios Petropoulos & Feng Li. (2023) Feature-based intermittent demand forecast combinations: accuracy and inventory implications. International Journal of Production Research 61:22, pages 7557-7572.
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Maximiliano Udenio, Eleni Vatamidou & Jan C. Fransoo. (2023) Exponential smoothing forecasts: taming the bullwhip effect when demand is seasonal. International Journal of Production Research 61:6, pages 1796-1813.
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Articles from other publishers (1)

Mike Nkongolo. (2023) Using ARIMA to Predict the Growth in the Subscriber Data Usage. Eng 4:1, pages 92-120.
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