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A cross-temporal hierarchical framework and deep learning for supply chain forecasting · Study

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ArticleA cross-temporal hierarchical framework and deep learning for supply chain forecasting

Sushil Punia2020

Article2020

A cross-temporal hierarchical framework and deep learning for supply chain forecasting

Sushil Punia · Surya Prakash Singh · Jitender Madaan

76 citations·0/0 files stored·Computers & Industrial Engineering

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Forecasting Techniques and Applications Supply Chain and Inventory Management Time Series Analysis and Forecasting

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References

2017Deep learning with long short-term memory networks for financial market predictions 2011Optimal combination forecasts for hierarchical time series 2018Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization 2015Supply chain forecasting: Theory, practice, their gap and the future 2017Forecasting with temporal hierarchies 2001Forecasting aggregate retail sales:2008Hierarchical forecasts for Australian domestic tourism 2007On the Benefits of Collaborative Forecasting Partnerships Between Retailers and Manufacturers

Cited by

2025MCDFN: supply chain demand forecasting via an explainable multi-channel data fusion network model 2021Forecasting hierarchical time series in supply chains: an empirical investigation 2025Deep learning for algorithmic trading: A systematic review of predictive models and optimization strategies 2025Application of artificial intelligence in demand planning for supply chains: a systematic literature review 2023A novel multi-phase hierarchical forecasting approach with machine learning in supply chain management

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Details

Year2020

Typearticle

Published2020-09-06

VenueComputers & Industrial Engineering

ISSN-L0360-8352

Languageen

Citations76

Files0 public / 0

ShelfForecasting Techniques and Applications

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doi10.1016/j.cie.2020.106796

openalex_workW3083526163

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