An artificial neural network approach for predicting area, production and productivity of Banana in Gujarat
Author(s):
Prity Kumari, DJ Parmar, Sathish Kumar M, YA Lad and AB Mahera
Abstract:
The present study steered to predicting area, production and productivity of banana in Gujarat by using different models. The secondary data on area, production and productivity of banana in Gujarat (1991-92 to 2017-18) were collected from Directorate of Horticulture, Gujarat. Time series secondary data on area, production and productivity of Banana were collected for the period 1958-59 to 2017-18. The collected data were analyzed in R Studio (version 3.5.2) software. Different Artificial Neural Network models employed to forecast area, production and productivity of fruits crops and also find out best models through comparison of all models 2:2s:1l, 2:3s:1l & 2:2s:1l ANN architectures models were best predicted area, production and productivity of banana in Gujarat with predicted value for 2018-19, 78.59 thousand hectares area, 6286.89 metric tonnes production and 55.29 metric tonnes per hectare productivity where area and production are likely to increase while productivity will go down in upcoming years.
How to cite this article:
Prity Kumari, DJ Parmar, Sathish Kumar M, YA Lad and AB Mahera. An artificial neural network approach for predicting area, production and productivity of Banana in Gujarat. The Pharma Innovation Journal. 2022; 11(4S): 816-821.