Imprecise parameters for near‐optimal control of stochastic SIV epidemic model
The change of parameters may influence the dynamic behaviors of epidemic diseases. Biological system parameters can also be changed due to diverse uncertainties such as lack of data and errors in the statistical approach. The problem of how to define and decide the optimal‐control strategies of epid...
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| Veröffentlicht in: | Mathematical methods in the applied sciences 2020-03, Vol.43 (5), p.2301-2321 |
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| creator | Wang, Zong Zhang, Qimin Meyer‐Baese, Anke |
| description | The change of parameters may influence the dynamic behaviors of epidemic diseases. Biological system parameters can also be changed due to diverse uncertainties such as lack of data and errors in the statistical approach. The problem of how to define and decide the optimal‐control strategies of epidemic diseases with imprecise parameters deserves further researches. The paper presents a stochastic susceptible, infected, and vaccinated (SIV) system that includes imprecise parameters. Firstly, we give the method of parameter estimates of the SIV model. Then, by using Ekeland's principle and Hamiltonian function, we obtain the sufficient conditions and necessary conditions of near‐optimal control of the SIV epidemic model with imprecise parameters. At last, numerical examples prove our theoretical results. |
| doi_str_mv | 10.1002/mma.6041 |
| format | Article |
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Biological system parameters can also be changed due to diverse uncertainties such as lack of data and errors in the statistical approach. The problem of how to define and decide the optimal‐control strategies of epidemic diseases with imprecise parameters deserves further researches. The paper presents a stochastic susceptible, infected, and vaccinated (SIV) system that includes imprecise parameters. Firstly, we give the method of parameter estimates of the SIV model. Then, by using Ekeland's principle and Hamiltonian function, we obtain the sufficient conditions and necessary conditions of near‐optimal control of the SIV epidemic model with imprecise parameters. At last, numerical examples prove our theoretical results.</description><identifier>ISSN: 0170-4214</identifier><identifier>EISSN: 1099-1476</identifier><identifier>DOI: 10.1002/mma.6041</identifier><language>eng</language><publisher>Freiburg: Wiley Subscription Services, Inc</publisher><subject>control ; Disease control ; Epidemics ; Hamiltonian functions ; Mathematical models ; Optimal control ; optimal stochastic control ; Parameter estimation ; stochastic systems and control ; systems theory</subject><ispartof>Mathematical methods in the applied sciences, 2020-03, Vol.43 (5), p.2301-2321</ispartof><rights>2019 John Wiley & Sons, Ltd.</rights><rights>2020 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2931-64cce794be0ac5b2f169a89d128dc4e3d477ebc9559e038d320cef9651c0c3e63</citedby><cites>FETCH-LOGICAL-c2931-64cce794be0ac5b2f169a89d128dc4e3d477ebc9559e038d320cef9651c0c3e63</cites><orcidid>0000-0002-6099-2799 ; 0000-0002-9938-0036</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fmma.6041$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmma.6041$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27903,27904,45553,45554</link.rule.ids></links><search><creatorcontrib>Wang, Zong</creatorcontrib><creatorcontrib>Zhang, Qimin</creatorcontrib><creatorcontrib>Meyer‐Baese, Anke</creatorcontrib><title>Imprecise parameters for near‐optimal control of stochastic SIV epidemic model</title><title>Mathematical methods in the applied sciences</title><description>The change of parameters may influence the dynamic behaviors of epidemic diseases. Biological system parameters can also be changed due to diverse uncertainties such as lack of data and errors in the statistical approach. The problem of how to define and decide the optimal‐control strategies of epidemic diseases with imprecise parameters deserves further researches. The paper presents a stochastic susceptible, infected, and vaccinated (SIV) system that includes imprecise parameters. Firstly, we give the method of parameter estimates of the SIV model. Then, by using Ekeland's principle and Hamiltonian function, we obtain the sufficient conditions and necessary conditions of near‐optimal control of the SIV epidemic model with imprecise parameters. At last, numerical examples prove our theoretical results.</description><subject>control</subject><subject>Disease control</subject><subject>Epidemics</subject><subject>Hamiltonian functions</subject><subject>Mathematical models</subject><subject>Optimal control</subject><subject>optimal stochastic control</subject><subject>Parameter estimation</subject><subject>stochastic systems and control</subject><subject>systems theory</subject><issn>0170-4214</issn><issn>1099-1476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp10M1KAzEQB_AgCtYq-AgBL162TrLZjxxL8aPQouDHNaSzs7hl06zJivTmI_iMPolb69XTMPDjP8yfsXMBEwEgr5yzkxyUOGAjAVonQhX5IRuBKCBRUqhjdhLjGgBKIeSIPcxdFwibSLyzwTrqKURe-8A3ZMP355fv-sbZlqPf9MG33Nc89h5fbewb5I_zF05dU5EbFucrak_ZUW3bSGd_c8yeb66fZnfJ4v52PpsuEpQ6FUmuEKnQakVgMVvJWuTalroSsqxQUVqpoqAV6izTBGlZpRKQap1nAgFTytMxu9jndsG_vVPszdq_h81w0kilSiW1kjCoy73C4GMMVJsuDO-ErRFgdn2ZoS-z62ugyZ5-NC1t_3VmuZz--h8oYmzR</recordid><startdate>20200330</startdate><enddate>20200330</enddate><creator>Wang, Zong</creator><creator>Zhang, Qimin</creator><creator>Meyer‐Baese, Anke</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><orcidid>https://orcid.org/0000-0002-6099-2799</orcidid><orcidid>https://orcid.org/0000-0002-9938-0036</orcidid></search><sort><creationdate>20200330</creationdate><title>Imprecise parameters for near‐optimal control of stochastic SIV epidemic model</title><author>Wang, Zong ; Zhang, Qimin ; Meyer‐Baese, Anke</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2931-64cce794be0ac5b2f169a89d128dc4e3d477ebc9559e038d320cef9651c0c3e63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>control</topic><topic>Disease control</topic><topic>Epidemics</topic><topic>Hamiltonian functions</topic><topic>Mathematical models</topic><topic>Optimal control</topic><topic>optimal stochastic control</topic><topic>Parameter estimation</topic><topic>stochastic systems and control</topic><topic>systems theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Zong</creatorcontrib><creatorcontrib>Zhang, Qimin</creatorcontrib><creatorcontrib>Meyer‐Baese, Anke</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><jtitle>Mathematical methods in the applied sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Zong</au><au>Zhang, Qimin</au><au>Meyer‐Baese, Anke</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Imprecise parameters for near‐optimal control of stochastic SIV epidemic model</atitle><jtitle>Mathematical methods in the applied sciences</jtitle><date>2020-03-30</date><risdate>2020</risdate><volume>43</volume><issue>5</issue><spage>2301</spage><epage>2321</epage><pages>2301-2321</pages><issn>0170-4214</issn><eissn>1099-1476</eissn><abstract>The change of parameters may influence the dynamic behaviors of epidemic diseases. Biological system parameters can also be changed due to diverse uncertainties such as lack of data and errors in the statistical approach. The problem of how to define and decide the optimal‐control strategies of epidemic diseases with imprecise parameters deserves further researches. The paper presents a stochastic susceptible, infected, and vaccinated (SIV) system that includes imprecise parameters. Firstly, we give the method of parameter estimates of the SIV model. Then, by using Ekeland's principle and Hamiltonian function, we obtain the sufficient conditions and necessary conditions of near‐optimal control of the SIV epidemic model with imprecise parameters. At last, numerical examples prove our theoretical results.</abstract><cop>Freiburg</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/mma.6041</doi><tpages>21</tpages><orcidid>https://orcid.org/0000-0002-6099-2799</orcidid><orcidid>https://orcid.org/0000-0002-9938-0036</orcidid></addata></record> |
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| source | Wiley Online Library Journals Frontfile Complete |
| subjects | control Disease control Epidemics Hamiltonian functions Mathematical models Optimal control optimal stochastic control Parameter estimation stochastic systems and control systems theory |
| title | Imprecise parameters for near‐optimal control of stochastic SIV epidemic model |
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