Forecasting Sugarcane Yield of India based on rough set combination approach

  • Haresh Kumar Sharma Department of Mathematics, Shree Guru Gobind Singh Tricentenary University, Gurugram, India
  • Kriti Kumari Department of Mathematics, Banasthali Vidyapith, Jaipur, Rajasthan, India
  • Samarjit Kar Department of Mathematics, National Institute of Technology Durgapur, West Bengal, India
Keywords: Sugarcane, Forecast, time series models, Rough set combination


This study applied a novel rough set combination approach for forecasting sugarcane production in India. The paper uses autoregressive integrated moving average (ARIMA), double exponential smoothing (DES) and Grey model (GM) to generate the single forecasts. Also, the weight coefficient is evaluated by underlying the rough set approach to combine the single forecasts obtained from different models. To validate our proposed analysis, Sugarcane from 1950 to 2011 was used for the overall empirical analysis and generate out-sample forecasts from 2012 to 2021 for the comparative analysis. Also, ARIMA (2, 1, 1) model is found more appropriate for forecasting Sugarcane production.


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How to Cite
Sharma, H. K., Kumari, K., & Kar, S. (2021). Forecasting Sugarcane Yield of India based on rough set combination approach. Decision Making: Applications in Management and Engineering, 4(2), 163-177.