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Crop production prediction using artificial neural network
M. Subash, S. Sawant, V. Kishore,
Published in Innovare Academics Sciences Pvt. Ltd
Volume: 7
Issue: 17
Pages: 2064 - 2072
With an 18 per cent of India's gross domestic production (GDP) and an employment to 50% of its workforce, agriculture is one of the most important sectors to the Indian Economy. The Indian food industry is rapidly growing ever after the green revolution and it has an increasing contribution to world food trade every year due to its immense potential for value addition. Various seasonal, economic and biological factors influence the crop production but unpredictable and incalculable changes in such factor's leads to huge losses in the market and to its stakeholders [1]. Thus, to minimize the loss, yield prediction is an important issue that needs to be addressed. Through this paper, we propose to predict various factors such as rainfall level, soil composition, weather and seasonal change values to an optimum accuracy to maximize the output of the crop production through simple neural network model. © 2020 Innovare Academics Sciences Pvt. Ltd. All rights reserved.
About the journal
JournalJournal of Critical Reviews
PublisherInnovare Academics Sciences Pvt. Ltd