Recent publications
Article
Barrow, D, Mitrovic, A, Holland, J, Ali, M, Kourentzes, N & Leva, S (ed.) 2024, 'Developing Personalised Learning Support for the Business Forecasting Curriculum: The Forecasting Intelligent Tutoring System', Forecasting, vol. 6, no. 1, pp. 204-223. https://doi.org/10.3390/forecast6010012
Barrow, D 2020, 'Automatic robust estimation for exponential smoothing: Perspectives from statistics and machine learning', Expert Systems with Applications, vol. 160, 113637. https://doi.org/10.1016/j.eswa.2020.113637
Kourentzes, N, Trapero, JR & Barrow, DK 2019, 'Optimising forecasting models for inventory planning', International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2019.107597
Kourentzes, N, Barrow, D & Petropoulos, F 2018, 'Another look at forecast selection and combination: Evidence from forecast pooling', International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2018.05.019
Barrow, D & Kourentzes, N 2018, 'The impact of special days in call arrivals forecasting: a neural network approach to modelling special days', European Journal of Operational Research, vol. 264, no. 3, pp. 967-977. https://doi.org/10.1016/j.ejor.2016.07.015
Kourentzes, N, Rostami-Tabar, B & Barrow, DK 2017, 'Demand forecasting by temporal aggregation: Using optimal or multiple aggregation levels?', Journal of Business Research, vol. 78, pp. 1-9. https://doi.org/10.1016/j.jbusres.2017.04.016
Barrow, DK & Crone, SF 2016, 'A comparison of AdaBoost algorithms for time series forecast combination', International Journal of Forecasting, vol. 32, no. 4, pp. 1103-1119. https://doi.org/10.1016/j.ijforecast.2016.01.006
Barrow, DK & Crone, SF 2016, 'Cross-validation aggregation for combining autoregressive neural network forecasts', International Journal of Forecasting, vol. 32, no. 4, pp. 1120-1137. https://doi.org/10.1016/j.ijforecast.2015.12.011
Barrow, DK & Kourentzes, N 2016, 'Distributions of forecasting errors of forecast combinations: Implications for inventory management', International Journal of Production Economics, vol. 177, pp. 24-33. https://doi.org/10.1016/j.ijpe.2016.03.017
Barrow, DK 2016, 'Forecasting intraday call arrivals using the seasonal moving average method', Journal of Business Research, vol. 69, no. 12, pp. 6088-6096. https://doi.org/10.1016/j.jbusres.2016.06.016
Kourentzes, N, Barrow, DK & Crone, SF 2014, 'Neural network ensemble operators for time series forecasting', Expert Systems with Applications, vol. 41, no. 9, pp. 4235-4244. https://doi.org/10.1016/j.eswa.2013.12.011
Mitrovic, A, Ohlsson, S & Barrow, DK 2013, 'The effect of positive feedback in a constraint-based intelligent tutoring system', Computers and Education, vol. 60, no. 1, pp. 264-272. https://doi.org/10.1016/j.compedu.2012.07.002
Conference contribution
Barrow, DK & Crone, SF 2013, Crogging (cross-validation aggregation) for forecasting - A novel algorithm of neural network ensembles on time series subsamples. in 2013 International Joint Conference on Neural Networks, IJCNN 2013., 6706740, 2013 International Joint Conference on Neural Networks, IJCNN 2013, Dallas, TX, United States, 4/08/13. https://doi.org/10.1109/IJCNN.2013.6706740
Barrow, DK, Crone, SF & Kourentzes, N 2010, An evaluation of neural network ensembles and model selection for time series prediction. in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010., 5596686, 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010, Barcelona, Spain, 18/07/10. https://doi.org/10.1109/IJCNN.2010.5596686
Review article
Petropoulos, F, Apiletti, D, Assimakopoulos, V, Babai, MZ, Barrow, DK, Ben taieb, S, Bergmeir, C, Bessa, RJ, Bijak, J, Boylan, JE, Browell, J, Carnevale, C, Castle, JL, Cirillo, P, Clements, MP, Cordeiro, C, Cyrino Oliveira, FL, De Baets, S, Dokumentov, A, Ellison, J, Fiszeder, P, Franses, PH, Frazier, DT, Gilliland, M, Gönül, MS, Goodwin, P, Grossi, L, Grushka-Cockayne, Y, Guidolin, M, Guidolin, M, Gunter, U, Guo, X, Guseo, R, Harvey, N, Hendry, DF, Hollyman, R, Januschowski, T, Jeon, J, Jose, VRR, Kang, Y, Koehler, AB, Kolassa, S, Kourentzes, N, Leva, S, Li, F, Litsiou, K, Makridakis, S, Martin, GM, Martinez, AB, Meeran, S, Modis, T, Nikolopoulos, K, Önkal, D, Paccagnini, A, Panagiotelis, A, Panapakidis, I, Pavía, JM, Pedio, M, Pedregal, DJ, Pinson, P, Ramos, P, Rapach, DE, Reade, JJ, Rostami-Tabar, B, Rubaszek, M, Sermpinis, G, Shang, HL, Spiliotis, E, Syntetos, AA, Talagala, PD, Talagala, TS, Tashman, L, Thomakos, D, Thorarinsdottir, T, Todini, E, Trapero Arenas, JR, Wang, X, Winkler, RL, Yusupova, A & Ziel, F 2022, 'Forecasting: theory and practice', International Journal of Forecasting, vol. 38, no. 3, pp. 705-871. https://doi.org/10.1016/j.ijforecast.2021.11.001
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