Predicting the soil profile through modified regression by discretisation algorithm for the crop yield in Trichy district, India. (2018)

• Record Type: Journal Article
• Authors: Geetha, M.C.S.; Shanthi, I. Elizabeth
• Is Part Of: International journal of grid and utility computing. Volume 9:Number 3(2018)
• Page Start: 235
• Page End: 242
• Publication Date: 2018
• Subjects: agriculture -- classifiers -- regression by discretisation -- soil -- Trichy district -- India; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

Abstract

Agriculture seems to be the most prime segment of the Tamil nadu State financial system, as around 70% of the residents are occupied in agriculture and associated activities for their source of revenue. But still, the state faces problems of resource-poor farmers, fragmentation of holdings, reliance on monsoon rain, and poor soil productivity. We have taken up the issue of predicting the yield level by analysing the soil characteristics for the particular soil. As gathering the information from an enormous volume of data is practically a complicated task in the recent circumstances, we have concentrated only on Trichy district and the soil data samples have been collected. The modified regression by discretisation was used for training and testing of the data sets and the results were explored in order to obtain the crop yield prediction for the soil. This study proves it's best for training soil data for classes' prediction.