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An improved fuzzy time-series method of forecasting based on L -- R fuzzy sets and its application

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  • Himadri Ghosh
  • S. Chowdhury
  • Prajneshu

Abstract

Classical time-series theory assumes values of the response variable to be ‘crisp’ or ‘precise’, which is quite often violated in reality. However, forecasting of such data can be carried out through fuzzy time-series analysis. This article presents an improved method of forecasting based on L -- R fuzzy sets as membership functions. As an illustration, the methodology is employed for forecasting India's total foodgrain production. For the data under consideration, superiority of proposed method over other competing methods is demonstrated in respect of modelling and forecasting on the basis of mean square error and average relative error criteria. Finally, out-of-sample forecasts are also obtained.

Suggested Citation

  • Himadri Ghosh & S. Chowdhury & Prajneshu, 2016. "An improved fuzzy time-series method of forecasting based on L -- R fuzzy sets and its application," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(6), pages 1128-1139, May.
    • Handle: RePEc:taf:japsta:v:43:y:2016:i:6:p:1128-1139
    DOI: 10.1080/02664763.2015.1092111
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    References listed on IDEAS

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    1. Singh, S.R., 2008. "A computational method of forecasting based on fuzzy time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 539-554.
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    Cited by:

    1. Tai Vovan & Luan Nguyenhuynh & Thuy Lethithu, 2022. "A forecasting model for time series based on improvements from fuzzy clustering problem," Annals of Operations Research, Springer, vol. 312(1), pages 473-493, May.
    2. Maigana Alhaji Bakawu, 2021. "Demographic Trends Forecasting: A Panacea for Sustainable Education Development Policies," International Journal of Science and Business, IJSAB International, vol. 5(7), pages 118-126.
    3. Thi-Nham Le & Thanh-Tuan Dang, 2022. "An Integrated Approach for Evaluating the Efficiency of FDI Attractiveness: Evidence from Vietnamese Provincial Data from 2012 to 2022," Sustainability, MDPI, vol. 14(20), pages 1-25, October.

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