Title
Theoretical Artificial Intelligence Based on Shannon Entropy to Identify Strains in Covid-19 Pandemic
Date Issued
01 January 2021
Access level
metadata only access
Resource Type
conference paper
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
Based in the fact that ongoing pandemic is caused by a kind of disorder, this paper employs the concept of Shannon entropy to model data of infections by Covid-19. The usage of this represents a proposal as a type of artificial intelligence that might be used in advanced softwares to perform instantaneous measurements of new infections. The presented theory is applied to the case of UK data, yielding an interesting matching. Therefore, it is seen that waves of pandemics can be explained in terms of apparition of strains and entropy.
Start page
45
End page
46
Language
English
OCDE Knowledge area
Enfermedades infecciosas Ingeniería eléctrica, Ingeniería electrónica Epidemiología
Scopus EID
2-s2.0-85125747960
ISBN of the container
9781665434126
Conference
Proceedings - 3rd International Conference on Transdisciplinary AI, TransAI 2021
Sources of information: Directorio de Producción Científica Scopus