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ArticleCombining probabilistic forecasts of intermittent demand

Shengjie Wang2024

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Articlegreen2024

Combining probabilistic forecasts of intermittent demand

Shengjie Wang · Yanfei Kang · Fotios Petropoulos

38 citations·0/0 files stored·European Journal of Operational Research

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Forecasting Techniques and Applications Supply Chain and Inventory Management Grey System Theory Applications

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References

2008Automatic Time Series Forecasting: The forecast Package for R 2019DeepAR: Probabilistic forecasting with autoregressive recurrent networks 2004Combination forecasts of output growth in a seven‐country data set 2002A state space framework for automatic forecasting using exponential smoothing methods 2022Forecasting: theory and practice 2014Probabilistic Forecasting 1972Forecasting and Stock Control for Intermittent Demands 2022M5 accuracy competition: Results, findings, and conclusions

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2020Elucidate structure in intermittent demand seriesarticle · 13 shared references 2019The Evolution of Forecast Density Combinations in Economicsother · 13 shared references 2020On the empirical performance of some new neural network methods for forecasting intermittent demandarticle · 13 shared references 2021Product sales probabilistic forecasting: An empirical evaluation using the M5 competition dataarticle · 13 shared references 2021Intermittent demand forecasting for spare parts: A Critical reviewarticle · 12 shared references 2021Forecasting intermittent and sparse time series: A unified probabilistic framework via deep renewal processesarticle · 12 shared references

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Year2024

Typearticle

Published2024-01-25

VenueEuropean Journal of Operational Research

ISSN-L0377-2217

Languageen

Citations38

Files0 public / 0

ShelfForecasting Techniques and Applications

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doi10.1016/j.ejor.2024.01.032

openalex_workW4391233944

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