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This document summarizes a research paper that proposes using a Least Squares Support Vector Machines (LS-SVM) model to predict future dengue outbreaks. The LS-SVM model is trained using past dengue case data and rainfall levels from five districts in Selangor, Malaysia. The prediction accuracy of the LS-SVM model is then compared to an artificial neural network model. The LS-SVM model achieved higher prediction accuracy and was faster computationally compared to the neural network model.

Author

Kira Kira

Language

EN