Optimal control by deep learning techniques and its applications on epidemic models.

Journal: Journal of mathematical biology
Published Date: Jan 25, 2023

Abstract

We represent the optimal control functions by neural networks and solve optimal control problems by deep learning techniques. Adjoint sensitivity analysis is applied to train the neural networks embedded in differential equations. This method can not only be applied in classic epidemic control problems, but also in epidemic forecasting, discovering unknown mechanisms, and the ideas behind can give new insights to traditional mathematical epidemiological problems.

Authors

  • Shuangshuang Yin
    Department of Applied Mathematics, School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China.
  • Jianhong Wu
    Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada.
  • Pengfei Song

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