Data-Driven Deep-Learning Algorithm for Asymptomatic COVID-19 Model with Varying Mitigation Measures and Transmission Rate
Epidemiological models with constant parameters may not capture satisfactory infection patterns in the presence of pharmaceutical and non-pharmaceutical mitigation measures during a pandemic, since infectiousness is a function of time. In this paper, an Epidemiology-Informed Neural Network algorithm...
Saved in:
Main Authors: | K. D. Olumoyin (Author), A. Q. M. Khaliq (Author), K. M. Furati (Author) |
---|---|
Format: | Book |
Published: |
MDPI AG,
2021-09-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Deep-Data-Driven Neural Networks for COVID-19 Vaccine Efficacy
by: Thomas K. Torku, et al.
Published: (2021) -
Data-Driven Deep Learning Neural Networks for Predicting the Number of Individuals Infected by COVID-19 Omicron Variant
by: Ebenezer O. Oluwasakin, et al.
Published: (2023) -
System- and Data-Driven Methods and Algorithms
Published: (2021) -
System- and Data-Driven Methods and Algorithms
Published: (2021) -
To vary or not to vary? Interpreting heart rate variability in soccer players
by: Fábio Y. Nakamura, et al.
Published: (2020)