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The paper proposes an intelligent irrigation framework for improving irrigation scheduling and crop productivity. FMIG-RF-SV is used for feature selection and SVM with Improved Crayfish Optimisation Algorithm is used for prediction, achieving 94.16% accuracy.
Agriculture is strongly affected by rainfall and weather variations. Climate change, environmental pressures, and limited land, labour and resources create a need for technology-enabled sustainable agricultural production.