Rice Yield prediction - a comparison between Enchanced Back Propagation Learning Algorithms

Abstract

Back Propagation algorithm(BP) has been popularly used to solve various problems, however it is shrouded with the problems of low convergence and instability. In recent years, improvements have been attempted to overcome the discrepancies aforementioned. In this study, we examine the performance of four enhanced BP algorithms to predict rice yield in MAD A plantation area in Kedah, Malaysia. A midst the four algorithms explored, Conjugate Gradient Descent exhibits the best performance.