Corn Yield Prediction Model with Deep Neural Networks for Smallholder Farmer Decision Support System

arXiv:2401.03768v2 Announce Type: replace
Abstract: Crop yield prediction has been modeled on the assumption that there is no interaction between weather and soil variables. However, this paper argues that an interaction exists, and it can be finely modelled using the Kendall Correlation coefficient. Given the nonlinearity of the interaction between weather and soil variables, a deep neural network regressor (DNNR) is carefully designed with consideration to the depth, number of neurons of the hidden layers, and the hyperparameters with their …

abstract arxiv correlation cs.ai cs.cy cs.hc cs.lg decision decision support however networks neural networks paper prediction support type variables weather