期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2019
卷号：19
期号：10
页码：31-36
出版社：International Journal of Computer Science and Network Security
摘要：This study has been planned to assess these inventive procedures such that significant relationship can be found by their applications to the various variables present in the data base. The couple of procedures like Na?ve Bayes, SVM, Random Forest, Ada-boost and Bagging are applied in the domain of agriculture were presented. The aim of this paper is to give the models that can identify the date palm cultivations where growth and production is likely to get affected due to adverse environmental factors by providing the structure for reliable date crop estimation forecasts. The result shows that the performance of Ada-boost-RF is best and the accuracy is 84% while the base learner RF is also good 83%.
