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Accuracy Assessment of Artificial Intelligence-Based Hybrid Models for Spare Parts Demand Forecasting in Mining Industry

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Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology – ISAT 2019 (ISAT 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1052))

Abstract

The paper addresses the problem of spare parts demand forecasting in mining industry. The paper proposes new hybrid models combining traditional forecasting techniques based on time series (ARIMA, SES, Holt’s model, TES, SMA, EMA, WMA, ZLEMA, SBA) with artificial intelligence-based methods. Three new approaches are developed - (1) hybrid forecasting econometric model, (2) hybrid forecasting artificial neural network model and (3) hybrid forecasting support vector machine model. The assessment of the proposed hybrid models is conducted by a comparison with traditional methods and is based on relative forecast error ex post and coefficient of determination. Empirical verification of the proposed models is built upon real data from an underground copper mine. The forecasts according to 9 traditional techniques and 3 hybrid models are computed for 10 cases.

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Authors and Affiliations

  1. Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, Wrocław, Poland

    Maria Rosienkiewicz

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  1. Maria Rosienkiewicz
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Correspondence to Maria Rosienkiewicz .

Editor information

Editors and Affiliations

  1. University of Applied Sciences in Nysa, Nysa, Poland

    Zofia Wilimowska

  2. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Leszek Borzemski

  3. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Jerzy Świątek

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Rosienkiewicz, M. (2020). Accuracy Assessment of Artificial Intelligence-Based Hybrid Models for Spare Parts Demand Forecasting in Mining Industry. In: Wilimowska, Z., Borzemski, L., Świątek, J. (eds) Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology – ISAT 2019. ISAT 2019. Advances in Intelligent Systems and Computing, vol 1052. Springer, Cham. https://doi.org/10.1007/978-3-030-30443-0_16

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