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On timeline of enhancing testing-capacity of COVID-19: A case study via an optimal replacement model

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dc.contributor.author Meththananda, R.G.U.I
dc.contributor.author Ganegoda, N.C.
dc.contributor.author Perera, S.S.N.
dc.contributor.author Erandi, K.K.W.H.
dc.contributor.author Jayathunga, Y.
dc.contributor.author Peiris, H.O.W.
dc.date.accessioned 2023-03-28T04:14:27Z
dc.date.available 2023-03-28T04:14:27Z
dc.date.issued 2022
dc.identifier.citation Meththananda, R.G.U.I , et al. (2022). On timeline of enhancing testing-capacity of COVID-19: A case study via an optimal replacement model. Journal of Process Control 105 (2021) 204–213. en_US
dc.identifier.uri http://dr.lib.sjp.ac.lk/handle/123456789/12609
dc.description.abstract Process of enhancing testing-capacity regarding COVID-19 is a topic of interest. This task of enhancing is constrained by socio-economic background of a country either in favorable or unfavorable ways. In this paper, we investigate timing of enhancing testing-capacity as an optimal problem, where the enhancement is quantified via number of tests as an instant measure and recovered portion as a long-term measure. The proposed work is structured analogous to an optimal machine replacement model based on a non-linear integral equation. Overall model is partially identifiable and compatible parameter estimations are carried out for a specific case study covering an early stage scenario. In addition, scenario development criteria on demand and effort for enhancing testing-capacity are introduced for predictions. In one numerical experiment, it is observed that frequency of enhancing testing-capacity starts decreasing after two increments indicating a favorable direction amidst effort constraints. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.subject COVID-19 Integral equation Optimal replacement Testing-capacity Fuzzy operator Parameter estimation en_US
dc.title On timeline of enhancing testing-capacity of COVID-19: A case study via an optimal replacement model en_US
dc.type Article en_US


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