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Fuzzy logic for the management of vaccination during pandemics: A spread-rate-based approach

IAES International Journal of Artificial Intelligence · Vol. 13 No. 3 (2024) · hlm. 2808–2815

DOI
10.11591/ijai.v13.i3.pp2808-2815
ISSN
2252-8938, 2089-4872
Terbit
2024-09-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Pandemics, such as coronavirus disease COVID-19 are known to cause massive damage to the world's economic growth and their impacts are serious and influence across every aspect of social structure. The most inevitable factor in responding to the disaster of pandemics is the right management in terms of allocating a limited vaccine supply. The focus of this research work is to utilize a fuzzy logic inference system in the allocation of vaccine doses to the regional authorities by a central authority. The objective is obtained by designing a system based on fuzzy logic that considers the spread rate as the input to infer the vaccination rate of the local population. This system makes it possible for sufficient doses of vaccines to be allotted to the prioritized regions where the severity of the spread rate is a concern and vaccines are not held up in regions where the severity of the spread rate is lesser. The designed system is verified using MATLAB software, which shows that this method can ensure an effective and efficient allocation of vaccination in the local regions and aid the fight against the disastrous spread of the disease.

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  • Jain University
  • Visvesvaraya Technological University
  • Shri Madhwa Vadiraja Institute of Technology and Management
  • Sahyadri College of Engineering & Management
  • Nitte University
  • KLS Gogte Institute of Technology
  • AISSMS Institute of Information Technology
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Rekan penulisOrganisasiArtikel bersama
Ezhilarasan GanesanJain University2
Sanjana PoojaryAfiliasi tidak diketahui2
T ThilagrajAfiliasi tidak diketahui2
Utkrishna Udesh NaikAfiliasi tidak diketahui2
R BharathAfiliasi tidak diketahui2
V P BasheerVisvesvaraya Technological University1
Ganesh AithalShri Madhwa Vadiraja Institute of Technology and Management1
Melwin D SouzaSahyadri College of Engineering & Management1
Ananth Prabhu GurpurAfiliasi tidak diketahui1
Ranjith BhatJain University1
Rajashree NambiarNitte University1
Akshatha NaikAfiliasi tidak diketahui1
Ashwini AshwiniAfiliasi tidak diketahui1
Navilgone Krishna VaishnaviAfiliasi tidak diketahui1
Ruchitha Kamath SubhashchandraAfiliasi tidak diketahui1
Trapthi TrapthiAfiliasi tidak diketahui1
Altaf Osman MulaniAISSMS Institute of Information Technology1
Swapna SiddamsettiKLS Gogte Institute of Technology1
Melwin D SouzaAfiliasi tidak diketahui1
S SubbaiahSRM Institute of Science and Technology1
S. RamyaM. Kumarasamy College of Engineering1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Fuzzy logic for the management of vaccination during pandemics: A spread-rate-based approach</dc:title>
	<dc:creator>Kareem, Abdul</dc:creator>
	<dc:creator>Kumara, Varuna</dc:creator>
	<dc:subject xml:lang="en-US">Fuzzy Logic</dc:subject>
	<dc:subject xml:lang="en-US">Fuzzy logic; Mamdani inference; Pandemic; Vaccination; MATLAB</dc:subject>
	<dc:description xml:lang="en-US">Pandemics, such as coronavirus disease COVID-19 are known to cause massive damage to the world's economic growth and their impacts are serious and influence across every aspect of social structure. The most inevitable factor in responding to the disaster of pandemics is the right management in terms of allocating a limited vaccine supply. The focus of this research work is to utilize a fuzzy logic inference system in the allocation of vaccine doses to the regional authorities by a central authority. The objective is obtained by designing a system based on fuzzy logic that considers the spread rate as the input to infer the vaccination rate of the local population. This system makes it possible for sufficient doses of vaccines to be allotted to the prioritized regions where the severity of the spread rate is a concern and vaccines are not held up in regions where the severity of the spread rate is lesser. The designed system is verified using MATLAB software, which shows that this method can ensure an effective and efficient allocation of vaccination in the local regions and aid the fight against the disastrous spread of the disease.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2024-09-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/24488</dc:identifier>
	<dc:identifier>10.11591/ijai.v13.i3.pp2808-2815</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 13, No 3: September 2024; 2808-2815</dc:source>
	<dc:source>2252-8938</dc:source>
	<dc:source>2089-4872</dc:source>
	<dc:source>10.11591/ijai.v13.i3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/24488/14089</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Institute of Advanced Engineering and Science</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>