首页|Researchers at Thiagarajar College of Engineering Have Published New Study Findi ngs on Machine Learning (Weather based paddy yield prediction using machine lear ning regression algorithms)
Researchers at Thiagarajar College of Engineering Have Published New Study Findi ngs on Machine Learning (Weather based paddy yield prediction using machine lear ning regression algorithms)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on artificial intelligence have bee n presented. According to news reporting out of Thiagarajar College of Engineeri ng by NewsRx editors, research stated, “Paddy is a major crop in India which is highly affected by the weather variables resulting in drastic reduction of its y ield; adverse all the variables drastically reduce the paddy yield.” Our news correspondents obtained a quote from the research from Thiagarajar Coll ege of Engineering: “In this research, machine learning model was developed for prediction of paddy yield production by linear regression (LR), random forest re gression (RFR), support vector regression (SVR), cat boost regression (CBR), and hybrid machine learning with variance inflation factor (VIF) LR-VIF, RFR-VIF, S VR-VIF, and CBR-VIF techniques. The dataset consists of variables (weather) for more than 15 years collected for the study area which is Madurai district, Tamil Nadu in India. Analysis was carried out by fixing 70% of data cal ibration & remaining 30% for validation in Jupyter n otebook (Python programming). Results showed that CBR-VIF performed having nRMSE value 1.23 to 1.40% for Madurai South, nRMSE value 0.56 to 1.40% for Melur, nRMSE value 1.10 to 1.25% for Usilampatti, and nRMSE va lue 0.75 to 1.10% for Thirumangalam.”
Thiagarajar College of EngineeringAlgo rithmsCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
