A Decomposition-Driven Deep Learning Model for Intelligent Irrigation Decision-Making
A hybrid model that combines a Convolutional Neural Network with Complete Ensemble Empirical Mode Decomposition with Adaptive Noise for irrigation classification and water conservation in agricultural fields is proposed for improving irrigation decision-making and promoting sustainable water management in agriculture.