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Plant Disease Prediction with AI Methods by IAES IJAI is a document available to read on EtoBox.

The document discusses improving plant disease prediction through clustering and classification algorithms. It proposes a model using k-nearest neighbors classification combined with k-efficient clustering, which integrates k-means and k-medoids clustering. The model is tested on a soybean disease dataset and results show it achieves 100% accuracy, outperforming other algorithms. In general, combining clustering and classification can help predict and control outbreaks of plant disease.

Author

IAES IJAI

Language

EN