Benchmarking Disease Modeling Techniques on the Philippines’ COVID-19 Dataset

• Main Authors: Pulmano, Christian, Fernandez, Proceso L, Jr
• 格式: text
• 出版: Archīum Ateneo 2023
• 主題: Mathematical Modeling; Parameter Estimation; ARIMA; COVID-19; Artificial Intelligence and Robotics; Data Science; Other Computer Sciences
• 在線閱讀: https://archium.ateneo.edu/discs-faculty-pubs/417; https://doi.org/10.5220/0011626400003414
• 機構: Ateneo De Manila University

The COVID-19 pandemic has emphasized the importance of timely and accurate prediction of disease outbreaks. Mathematical disease models can help simulate the trajectory of diseases and guide policymakers in identifying priorities and gaps in current policies. This study evaluates the performance, on...