Chen’s model to understand the invariant fuzzy time series model through maize production in India

Abstract

The present study has applied a time-invariant fuzzy time series model for maize Production in India. Most of the time series data is forecasted using AR and ARIMA models but the present study considered the Chen fuzzy time series model to understand fuzzy time series and endeavour to forecast. Generally, fuzzy models are based on uncertainty, non-probabilistic and linguistic variables. The maize production of India during 1951-2020 data was divided into seven subsets. The subsets are equal intervals. Chen's model has used arithmetic operations for fuzzy logic relations and forecasting. The accuracy of the model was measured by Root Mean Square Error (1949.93) and Mean Absolute Percentage Error (25.86). The Chen model will give impetus to the higher-order fuzzy time series model.