A Comparative Analysis of Price Forecasting Models for Black Pepper
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Authors
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Akshaya Ajith
College of Agriculture, Kerala Agricultural University, Vellanikkara
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Sajitha Vijayan M.
College of Agriculture, Kerala Agricultural University, Vellanikkara
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Dayana David
College of Agriculture, Kerala Agricultural University, Vellanikkara
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Pratheesh P.
College of Agriculture, Kerala Agricultural University, Vellanikkara
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Anil Kuruvila
Kerala Agricultural University, Vellayani, Thiruvananthapuram
Keywords:
Garbled black pepper; SARIMA; TDNN; Forecasting.Abstract
Black pepper being a perennial crop, the significant fluctuations in prices throughout the year pose a considerable challenge for both farmers and consumers. It is essential to understand the extent to which these price variations can be predicted in the near future to formulate pertinent policy recommendations. Consequently, the modelling and forecasting of time series data related to black pepper price hold paramount significance. Monthly price of garbled black pepper used for forecasting the price using Seasonal Autoregressive Moving Average model (SARIMA) and Time-delay Neural Network (TDNN) models. Comparison of models based on the accuracy measures, revealed TDNN as the best model for forecasting monthly price of black pepper.
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