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Stefan cel Mare
University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  3/2020 - 3

An Artificial Immune System Approach for a Multi-compartment Queuing Model for Improving Medical Resources and Inpatient Bed Occupancy in Pandemics

BELCIUG, S. See more information about BELCIUG, S. on SCOPUS See more information about BELCIUG, S. on IEEExplore See more information about BELCIUG, S. on Web of Science, BEJINARIU, S.-I. See more information about  BEJINARIU, S.-I. on SCOPUS See more information about  BEJINARIU, S.-I. on SCOPUS See more information about BEJINARIU, S.-I. on Web of Science, COSTIN, H. See more information about COSTIN, H. on SCOPUS See more information about COSTIN, H. on SCOPUS See more information about COSTIN, H. on Web of Science
 
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Download PDF pdficon (1,269 KB) | Citation | Downloads: 292 | Views: 585

Author keywords
artificial intelligence, evolutionary computation, hospitals, optimization, queueing analysis

References keywords
optimization(22), inspired(12), nature(9), algorithms(9), intelligence(8), artificial(7), systems(6), gorunescu(6), algorithm(6), selection(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2020-08-31
Volume 20, Issue 3, Year 2020, On page(s): 23 - 30
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.03003
Web of Science Accession Number: 000564453800003
SCOPUS ID: 85090354940

Abstract
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In the context of the Covid-19 pandemic the pressure that is put on the medical systems is increasing exponentially. Healthcare systems resources are in general scarce, and hence they require policies that ensure the optimal usage of beds and utilization costs. The aim of this study is to explore how artificial immune system approaches for a multi-queuing model may aid the hospital managers improve their resources. The proposed system outlines the route of Covid-19 patients in the intensive care unit (ICU), the compartmental model proposes a reasonable composition of the ICU, considering the queuing parameters, while the artificial immune system optimizes the needed resources (beds plus associated costs). The methodology was demonstrated through a simulation based on real data collected from official sources.


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References Weight

Web of Science® Citations for all references: 33,788 TCR
SCOPUS® Citations for all references: 11,885 TCR

Web of Science® Average Citations per reference: 719 ACR
SCOPUS® Average Citations per reference: 253 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2021-07-23 06:59 in 213 seconds.




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