National Academy of Agricultural Sciences (NAAS)
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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706 Issues : 12 per year Publisher : Excellent Publishers Email : editorijcmas@gmail.com / submit@ijcmas.com Editor-in-chief: Dr.M.Prakash Index Copernicus ICV 2018: 95.39 NAAS RATING 2020: 5.38 |
Time series prediction is a vital problem in many applications in nature science, agriculture, engineering and economics. The objective of the study is to examine the flexibility of artificial neural network model (ANN) in time series forecasting by comparing with classical time series ARIMA model. The data consist of area and production of Pearl millet (bajra) crop area (‘000 ha) and production (‘000 MT) from 1955-56 to 2014-15 were collected from “Agricultural Statistics at a Glance 2014-15, Karnataka, India were used in the study to demonstrate the effectiveness of the model. The experiment shows that ANN model outperform the ARIMA Models based on root mean (RMSE), MAPE and MSE.
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