The oilseed crop yield prediction using Machine learning Algorithms
*1C. Mithra, *2A. Suhasini and *3S. Jothilakshmi
1&2Department of Computer Science and Engineering, Annamalai University, Annamalai Nagar-608001 (India) *1mithrac.official@gmail.com *2suha_babu@yahoo.com 3Department of Information Technology, Annamalai University, Annamalai Nagar-608001 (India) *3jothi.sekar@gmail.com
ABSTRACT
Agriculture provides significant economic support in India. Population growth is the most serious threat to food security. Population growth raises demand, requiring farmers to produce more to increase supply. Crop yield prediction technology can assist farmers in producing more yields. The primary goal of this study is to forecast oilseed crops yield for various districts of Tamil Nadu state. Machine learning classification algorithms are used to forecast oilseed crops yield. The actual yield data from 1961 to 2007 years are used as a training set and from 2008 to 2019 as a validation set. The results of the proposed algorithm are compared with those of existing algorithms namely linear regression, Support Vector Machine, Naive Bayes, and K-Nearest Neighbour, and an accuracy of 86.3%, 83.33%, 80.3%, and 77.56% respectively is observed. The actual and predicted oilseed crop yields from 1961 to 2019 are analysed for the yield forecast model, and the error percentages with underestimated and overestimated predictions for the various districts of Tamil Nadu are calculated. According to the study, the results of the linear regression are found to be superior to those of other algorithms. The study also assists farmers by providing a recommendation system to decide which crop to plant in a specific area and time. 1Research Scholar, 2Professor, 3Associate Professor