AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A comparative crop yield forecasting framework that combines agricultural and environmental variables with multi-model evaluation, cross-validation, feature-importance analysis, and multiple error metrics is developed.
Crop yield prediction is essential for improving agricultural productivity, resource management, and food security in the face of climate change and increasing population demands [1], [5]. Recent advances in Machine Learning (ML) and Deep Learning (DL) have significantly enhanced the accuracy of crop yield forecasting...
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