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New research tackles intermittent demand forecasting challenges · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Two new research papers explore the challenges of intermittent demand forecasting, where demand occurs infrequently and time series often contain many zero observations. The first paper, "Accuracy Is Not Service," introduces a decision-aware benchmark and finds that traditional accuracy metrics do not always correlate with actual service levels in contract logistics. It also details a correction for the Chronos-2 Forecasting Model that significantly improves fill rates. The second paper, "Are Gradient Boosting Models Suitable for Intermittent Demand Forecasting?", investigates the effectiveness of gradient-boosting models, concluding that while they underperform individually, they can enhance specialized methods when used in ensembles. AI

IMPACT These papers highlight the limitations of standard forecasting metrics and explore ensemble methods, potentially improving inventory management and operational efficiency in industries with intermittent demand.

RANK_REASON Two academic papers published on arXiv discussing forecasting methods.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New research tackles intermittent demand forecasting challenges · 2 sources tracked

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Two academic papers published on arXiv discussing forecasting methods.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Joo Ern Chin, Shih-Fen Cheng, Aldy Gunawan ·

    Accuracy Is Not Service: A Decision-Aware Benchmark for Intermittent-Demand Forecasting

    arXiv:2609.13840v1 Announce Type: new Abstract: A contract-logistics spare-parts operator is paid on order-level service: an order counts only if every requested line is fulfilled, yet forecasters are selected based on line-level forecast accuracy. This disconnect matters when de…

  2. arXiv cs.LG TIER_1 English(EN) · Vladislav Kislinskii, Mazhar Hameed ·

    Are Gradient Boosting Models Suitable for Intermittent Demand Forecasting?

    arXiv:2609.14718v1 Announce Type: new Abstract: Demand forecasting is critical in modern industry, offering opportunities to reduce costs and gain competitive advantage through improved inventory management. However, forecasting becomes particularly challenging for products with …

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