About: A novel control set-valued approach with application to epidemic models

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: A novel control set-valued approach with application to epidemic models Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A novel control set-valued approach with application to epidemic models
Creator	Boujallal, Lahoucine Elhia, Mohamed Balatif, ·
Source	Medline; PMC
abstract	This work is considered in the framework of studies dedicated to the control problems, especially in epidemiology where the scientist are concerned to develop effective control strategies to minimize the number of infected individuals. In this paper, we set this problem as an asymptotic target control problem under mixed state-control constraints, for a general class of ordinary differential equations that model the temporal evolution of disease spread. The set of initial data, from which the number of infected people decrease to zero, is generated by a new type of Lyapunov functions defined in the sense of viability theory. The associated controls are provided via selections of adequately designed feedback map. The existence of such selections is improved by using Micheal selection theorem. Finally, an application to the SIRS epidemic model, with numerical simulations, is given to show the efficiency of our approach. To the best of our knowledge, our work is the first one that used a set-valued approach based on the viability theory to deal with an epidemic control problem.
has issue date	2020-07-13(xsd:dateTime)
bibo:doi	10.1007/s12190-020-01392-x
bibo:pmid	32837465
has license	no-cc
sha1sum (hex)	5211a96115e408a2ac2eced159e533e8b57acaa4
schema:url	https://doi.org/10.1007/s12190-020-01392-x
resource representing a document's title	A novel control set-valued approach with application to epidemic models
has PubMed Central identifier	PMC7355539
has PubMed identifier	32837465
schema:publication	J Appl Math Comput
resource representing a document's body	covid:5211a96115e408a2ac2eced159e533e8b57acaa4#body_text
is schema:about of	named entity 'OUR APPROACH' named entity 'PROBLEMS' named entity 'DISEASE SPREAD' named entity 'PROVIDED' named entity 'EFFECTIVE' named entity 'mathematical model' named entity 'lsc' named entity 'epidemiological models' named entity 'significant difference' named entity 'epidemic model' named entity 'set-valued analysis' named entity 'epidemic' named entity 'force of infection' named entity 'Euclidean space' named entity 'non-linear control' named entity 'contingent cone' named entity 'epidemic' named entity 'global pandemic' named entity 'viruses' named entity 'public health' named entity 'epidemic model' named entity 'Michael selection theorem' named entity 'set-valued analysis' named entity 'vector' named entity 'Optimal control theory' named entity 'viability theory' named entity 'Tuberculosis' named entity 'complex systems' named entity 'lsc' named entity 'epidemic' named entity 'W. O. Kermack' named entity 'virus' named entity 'lsc' named entity 'Lyapunov function' named entity 'ordinary differential equations' named entity 'epidemiology' named entity 'evolution' named entity 'epidemic model' named entity 'initial data' named entity 'contingent cone' named entity 'Lyapunov function' named entity 'immunotherapy' named entity 'lsc' named entity 'Lyapunov function' named entity 'epidemics' named entity 'R N' named entity '14,000' named entity 'resource allocation' named entity 'Euclidean space' named entity 'divided into classes' named entity 'linear operator' named entity 'infectious disease' named entity 'non-linear' named entity 'prevent the spread' named entity 'closed subset' named entity 'control theory' named entity 'contingent cone' named entity 'incubation' named entity 'epidemiological models' named entity 'death rate' named entity 'lsc' named entity 'Tuberculosis' named entity 'preventive measures' named entity 'epidemiologists' named entity 'infectious diseases' named entity 'compartment models' named entity 'epidemiological models' named entity 'Optimal control' named entity 'epidemic' named entity 'epidemiological' named entity 'First World War' named entity 'infectious diseases' named entity 'Lyapunov functions' named entity 'Lyapunov function' named entity 'lsc' named entity 'differential operator' named entity '11,000' named entity 'vaccination' named entity 'infectious diseases'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software