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A type-II fuzzy collaborative forecasting approach for productivity forecasting under an uncertainty environment

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Abstract

Forecasting factory productivity is a critical task. However, it is not easy owing to the uncertainty of productivity. Existing methods often forecast productivity using a fuzzy number. However, the range of a fuzzy productivity forecast is wide owing to the consideration of extreme cases. In this study, a fuzzy collaborative forecasting approach is proposed to forecast factory productivity using a type-II fuzzy number and by narrowing the forecast’s range. The outer section of the type-II fuzzy number determines the range of productivity, while the inner section is defuzzified to derive the most likely value. Based on the experimental results, the proposed methodology surpassed existing methods in improving forecasting precision and accuracy, with a reduction in the mean absolute percentage error (MAPE) of up to 74%.

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Acknowledgements

This study was sponsored by the Ministry of Science and Technology, Taiwan.

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Authors and Affiliations

  1. Department of Industrial Engineering and Management, National Chiao Tung University, 1001 University Road, Hsinchu, Taiwan

    Toly Chen

  2. Department of Aeronautical Engineering, Chaoyang University of Technology, Taichung, Taiwan

    Yu-Cheng Wang

  3. Department of Industrial Engineering and Management, National Chin-Yi University of Technology, 57, Sec. 2, Zhongshan Rd., Taiping, Taichung, 411, Taiwan

    Min-Chi Chiu

Authors
  1. Toly Chen
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  2. Yu-Cheng Wang
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  3. Min-Chi Chiu
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Correspondence to Yu-Cheng Wang.

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Chen, T., Wang, YC. & Chiu, MC. A type-II fuzzy collaborative forecasting approach for productivity forecasting under an uncertainty environment. J Ambient Intell Human Comput 12, 2751–2763 (2021). https://doi.org/10.1007/s12652-020-02435-8

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  • DOI: https://doi.org/10.1007/s12652-020-02435-8

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