A NEW CROP YIELD PREDICTION SYSTEM USING RANDOM FOREST COMBINED WITH LEAST SQUARES SUPPORT VECTOR MACHINE

R Mythili
2020 JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES  
Predominantly in India, Agriculture is the most significant income generating segments and also a wellspring of endurance. Various occasional, financial and natural incidents impact the yield creation, yet erratic changes in these cases lead to an incredible misfortune for the Farmers. These dangers are to be decreased by utilizing reasonable mining methodologies on the identified data of soil type, temperature, environmental weights, mugginess and yield type. While, harvest and climate gauging
more » ... and climate gauging can be anticipated by getting valuable bits of knowledge from this agricultural information that guides the Farmers to choose the yield, meanwhile they may need to plant for the expected year prompting extreme benefits. This paper presents an overview of different calculations utilized for climate, crop yield, and harvest forecast of the proposed crop yield prediction method using Least Squares Support Vector Machine (LS-SVM).
doi:10.26782/jmcms.2020.05.00008 fatcat:65aa63ninzcvfh2gyq77ctkqnu