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Theoretical Paper

Forecasting for intermittent demand: the estimation of an unbiased average

, &
Pages 588-592 | Received 01 Apr 2004, Accepted 01 May 2005, Published online: 21 Dec 2017

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Giacomo Sbrana. (2023) Modelling intermittent time series and forecasting COVID-19 spread in the USA. Journal of the Operational Research Society 74:2, pages 465-475.
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A A Syntetos, M Z Babai, Y Dallery & R Teunter. (2009) Periodic control of intermittent demand items: theory and empirical analysis. Journal of the Operational Research Society 60:5, pages 611-618.
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A A Syntetos, J E Boylan & S M Disney. (2009) Forecasting for inventory planning: a 50-year review. Journal of the Operational Research Society 60:sup1, pages S149-S160.
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R Fildes, K Nikolopoulos, S F Crone & A A Syntetos. (2008) Forecasting and operational research: a review. Journal of the Operational Research Society 59:9, pages 1150-1172.
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Nachiketas Waychal, Arnab Kumar Laha & Ankur Sinha. An adaptive multi-objective optimal forecast combination and its application for predicting intermittent demand. Journal of the Operational Research Society 0:0, pages 1-13.
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Diksha Shrivastava, Sarthak Pujari, Yatin Katyal, Siddhartha Asthana, Chandrudu K & Aakashdeep Singh. (2023) INFRANET: Forecasting intermittent time series using DeepNet with parameterized conditional demand and size distribution. INFRANET: Forecasting intermittent time series using DeepNet with parameterized conditional demand and size distribution.
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M Z Babai, A Tsadiras & C Papadopoulos. (2020) On the empirical performance of some new neural network methods for forecasting intermittent demand. IMA Journal of Management Mathematics 31:3, pages 281-305.
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Tugce EKİZ YİLMAZ, Güçkan YAPAR & İdil YAVUZ. (2019) COMPARISON OF ATA METHOD AND CROSTON BASED METHODS ON FORECASTING OF INTERMITTENT DEMANDKESİKLİ TALEPLERİN TAHMİNLENMESİNDE ATA METOT VE CROSTON TEMELLİ METOTLARIN KARŞILAŞTIRILMASI. Mugla Journal of Science and Technology 5:2, pages 49-55.
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Sha Zhu, Rommert Dekker, Willem van Jaarsveld, Rex Wang Renjie & Alex J. Koning. (2017) An improved method for forecasting spare parts demand using extreme value theory. European Journal of Operational Research 261:1, pages 169-181.
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Clint L.P. Pennings, Jan van Dalen & Erwin A. van der Laan. (2017) Exploiting elapsed time for managing intermittent demand for spare parts. European Journal of Operational Research 258:3, pages 958-969.
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Adriano O. Solis. 2016. Supply Management Research. Supply Management Research 79 95 .
Ming Ding, Xiao-Sheng Si, Qi Zhang & Tianmei Li. (2015) An adaptive spare parts demand forecasting method based on degradation modeling. An adaptive spare parts demand forecasting method based on degradation modeling.
Aris A. Syntetos, M. Zied Babai & Everette S. GardnerJr.Jr.. (2015) Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping. Journal of Business Research 68:8, pages 1746-1752.
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Nikolaos Kourentzes. (2014) On intermittent demand model optimisation and selection. International Journal of Production Economics 156, pages 180-190.
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D. Lengu, A.A. Syntetos & M.Z. Babai. (2014) Spare parts management: Linking distributional assumptions to demand classification. European Journal of Operational Research 235:3, pages 624-635.
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Matthew Lindsey & Robert Pavur. 2013. Advances in Business and Management Forecasting. Advances in Business and Management Forecasting 185 195 .
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Nezih Altay, Lewis A. Litteral & Frank Rudisill. (2012) Effects of correlation on intermittent demand forecasting and stock control. International Journal of Production Economics 135:1, pages 275-283.
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Ulrich Küsters & Jan Speckenbach. 2012. Prognoserechnung. Prognoserechnung 75 108 .
Wenbin Wang & Aris A. Syntetos. (2011) Spare parts demand: Linking forecasting to equipment maintenance. Transportation Research Part E: Logistics and Transportation Review 47:6, pages 1194-1209.
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Aris A. Syntetos & John E. Boylan. 2011. Service Parts Management. Service Parts Management 1 30 .
Zhang Jiantong & Lv Biyu. (2009) Forecasting Intermittent Demand Based on Grey Theory. Forecasting Intermittent Demand Based on Grey Theory.
John E. Boylan & Aris A. Syntetos. 2008. Complex System Maintenance Handbook. Complex System Maintenance Handbook 479 506 .
Ebenezer Afrifa-Yamoah & Ute A. Mueller. (2021) Modeling Digital Camera Monitoring Count Data with Intermittent Zeros for Short-Term Prediction. SSRN Electronic Journal.
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