Publication Type : Journal Article
Publisher : Journal of Advanced Research in Dynamical and Control Systems
Source : Journal of Advanced Research in Dynamical and Control Systems, Volume 10, Issue 3, p.991-995 (2018)
Url : https://www.scopus.com/record/display.uri?eid=2-s2.0-85060027567&origin=resultslist
Keywords : C4.5, Crop prediction, GDP, Naive Bayes, Yield prediction
Campus : Mysuru
School : School of Arts and Sciences
Department : Computer Science
Year : 2018
Abstract : The growth of GDP (Gross Domestic Product) largely depends on the growth in agriculture. The total food grains produced in 2017 has been estimated to 275.68 million tons 6.5% lowest in last four years. The reasons are more like 60% of the land is under soil degradation etc. Prediction of crop is much popular among farmers these days to know the yield they can harvest. Machine learning is changing modern agriculture. This work uses machine learning techniques to predict the yield of crop based on their soil test report dataset. Here we are using Naive Bayes algorithm to predict the crop type and its subtype or crop which suits for the soil and this is done based on the soil test report. We are using C4.5 algorithm to predict the yield of the crop. © 2018, Institute of Advanced Scientific Research, Inc.. All rights reserved.
Cite this Research Publication : Madesh M. and V., K., “A systematic framework for prediction of crop yield of suitable crop”, Journal of Advanced Research in Dynamical and Control Systems, vol. 10, no. 3, pp. 991-995, 2018.