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International Conference on Case-Based Reasoning

ICCBR 2022: Case-Based Reasoning Research and Development pp 365–379Cite as

Forecasting for Sustainable Dairy Produce: Enhanced Long-Term, Milk-Supply Forecasting Using k-NN for Data Augmentation, with Prefactual Explanations for XAI

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13405))

Abstract

Accurate milk supply forecasting for the dairy sector, covering 1000 s of farms with low resolution data, is a key challenge in achieving a sustainable, precision agriculture that can improve farm management, balancing costs, energy use and environmental protection. We show that case-based reasoning (CBR) can meet this sustainability challenge, by supplementing a time series prediction model on a full-year-forecasting task. Using a dataset of three years of milk supply from Irish dairy farms (N = 2,479), we produce accurate full-year forecasts for each individual farm, by augmenting that farm’s data with data from nearest-neighboring farms, based on the similarity of their time series profiles (using Dynamic Time Warping). A study comparing four methods (Seasonal Naïve, LSTM, Prophet, \(Prophet^{NN}\)) showed that the method using CBR data-augmentation \((Prophet^{NN})\) outperformed the other evaluated methods. We also demonstrate the utility of CBR in providing farmers with novel prefactual explanations for forecasting that could help them to realize actions that could boost future milk yields and profitability.

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Acknowledgements

This publication has emanated from research conducted with the financial support of (i) Science Foundation Ireland (SFI) to the Insight Centre for Data Analytics under Grant Number 12/RC/2289_P2 and (ii) SFI and the Department of Agriculture, Food and Marine on behalf of the Government of Ireland under Grant Number 16/RC/3835 (VistaMilk).

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Authors and Affiliations

  1. School of Computer Science, University College Dublin, Dublin, Ireland

    Eoin Delaney, Derek Greene & Mark T. Keane

  2. Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland

    Eoin Delaney, Derek Greene & Mark T. Keane

  3. VistaMilk SFI Research Centre, Cork, Ireland

    Eoin Delaney, Derek Greene, Laurence Shalloo & Mark T. Keane

  4. Teagasc, Animal and Grassland Research Centre, Cork, Ireland

    Laurence Shalloo

  5. ICBF, Cork, Ireland

    Michael Lynch

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  1. Eoin Delaney
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Correspondence to Eoin Delaney .

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Editors and Affiliations

  1. University College Dublin, Dublin, Ireland

    Mark T. Keane

  2. The Robert Gordon University, Aberdeen, UK

    Nirmalie Wiratunga

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Delaney, E., Greene, D., Shalloo, L., Lynch, M., Keane, M.T. (2022). Forecasting for Sustainable Dairy Produce: Enhanced Long-Term, Milk-Supply Forecasting Using k-NN for Data Augmentation, with Prefactual Explanations for XAI. In: Keane, M.T., Wiratunga, N. (eds) Case-Based Reasoning Research and Development. ICCBR 2022. Lecture Notes in Computer Science(), vol 13405. Springer, Cham. https://doi.org/10.1007/978-3-031-14923-8_24

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  • DOI: https://doi.org/10.1007/978-3-031-14923-8_24

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