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Results for Temporal aggregation

Publications & Outputs

  1. Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption

    Spiliotis, E., Petropoulos, F., Kourentzes, N. & Assimakopoulos, V., 21/12/2019, In : Applied Energy. 261, 12 p., 114339.

    Research output: Contribution to journalJournal article

  2. Cross-temporal coherent forecasts for Australian tourism

    Kourentzes, N. & Athanasopoulos, G., 31/03/2019, In : Annals of Tourism Research. 75, p. 393-409 17 p.

    Research output: Contribution to journalJournal article

  3. The impact of temporal aggregation on supply chains with ARMA(1,1) demand processes

    Rostami-Tabar, B., Babai, M. Z., Ali, M. & Boylan, J. E., 16/03/2019, In : European Journal of Operational Research. 273, 3, p. 920-932 13 p.

    Research output: Contribution to journalJournal article

  4. Demand forecasting by temporal aggregation: using optimal or multiple aggregation levels?

    Kourentzes, N., Rostami-Tabar, B. & Barrow, D., 09/2017, In : Journal of Business Research. 78, p. 1-9 9 p.

    Research output: Contribution to journalJournal article

  5. Another look at estimators for intermittent demand

    Petropoulos, F., Kourentzes, N. & Nikolopoulos, K., 11/2016, In : International Journal of Production Economics. 181 , Part A, p. 154-161 8 p.

    Research output: Contribution to journalJournal article

  6. Forecasting with multivariate temporal aggregation: the case of promotional modelling

    Kourentzes, N. & Petropoulos, F., 11/2016, In : International Journal of Production Economics. 181, Part A, p. 145-153 9 p.

    Research output: Contribution to journalJournal article

  7. On the performance of overlapping and non-overlapping temporal demand aggregation approaches

    Boylan, J. E. & Babai, M. Z., 11/2016, In : International Journal of Production Economics. 181, Part A, p. 136-144 9 p.

    Research output: Contribution to journalJournal article

  8. Forecast horizon aggregation in integer autoregressive moving average (INARMA) models

    Mohammadipour, M. & Boylan, J., 1/12/2012, In : Omega: The International Journal of Management Science. 40, 6, p. 703-712 10 p.

    Research output: Contribution to journalJournal article

  9. Improving the performance of popular supply chain forecasting techniques

    Spithourakis, G., Petropoulos, F., Babai, M., Nikolopoulos, K. & Assimakopoulos, V., 2011, In : Supply Chain Forum: An International Journal. 12, 4, p. 16-25 10 p.

    Research output: Contribution to journalJournal article