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This study investigates the use of Artificial Intelligence (AI) models to analyze and optimize agricultural productivity in Nigeria, focusing on four key crops in Anambra State. It developed and compared three predictive models—Artificial Neural Network (ANN), Response Surface Method (RSM), and Linear Regression—using 13 years of historical data, concluding that the ANN model outperformed the others in predicting crop yields. The findings highlight the potential of AI to enhance decision-making and resource

Author

Alex Adams

Language

EN