Research Article
BibTex RIS Cite
Year 2021, Volume: 4 Issue: 2, 58 - 67, 31.08.2021

Abstract

References

  • [1] Republic of Turkey Ministry of Health Directorate General of Public Health, 2020. Covid-19 Scientific Advisory Board Study, Access Link : https://covid19.saglik.gov.tr/Eklenti/39551/0/covid-19rehberigenelbilgilerepidemiyolojivetanipdf.pdf.
  • [2]. Singh R., Avikal, S., 2020. COVID-19: A decision-making approach for prioritization of preventive activities, International Journal of Healthcare Management, 13:3, 257-262, DOI: 10.1080/20479700.2020.1782661.
  • [3]. World Health Organization (WHO), 2019. Coronavirus disease (COVID-19): How is transmitted?, Access Date: 17 August 2021.
  • [4]. Google News, 2019. Access Link : (https://news.google.com/covid19/map?hl=tr&mid=%2Fm%2F01znc_&gl=TR&ceid=TR%3Atr), Access Date: 17 August 2021
  • [5] Zhou Y, Yang Y, Huang J, Jiang S, Du L., 2019. Advances in MERS-CoV Vaccines and Therapeutics Based on the Receptor-Binding Domain. Viruses. Pp :11(1).
  • [6] Samaddar, S., Nargundkar, S., ve Daley, M., 2006. Inter-organizational information sharing: The role of supply network configuration and partner goal congruence, European Journal of Operational Research, 174(2), 744-765.
  • [7] Arji G, Ahmadi H, Nilashi M, Rashid T, Ahmed O, Aljojo N, Zainol A., 2019. Fuzzy logic approach for infectious disease diagnosis: A methodical evaluation, literature and classification. Biocybernetics and biomedical engineering, 39(4), 937–955.
  • [8] Adwibowo, A., 2020. Fuzzy logic assisted COVID 19 safety assessment of dental care, medRxiv.
  • [9] Kubat C., 2017. Matlab Artificial Intelligence and Engineering Applications, Third Edition, Abaküs Publications, 620-666.
  • [10] Bing W., Tingting C., Tsz Leung Y., Yang W., 2020. Fuzzy logic based dynamic decision-making system for intelligent navigation strategy within inland traffic separation schemes, Ocean Engineering, (Vol. 197:106909), doi.org/10.1016/j.oceaneng.2019.106909.
  • [11] Sivanandam, S. N., Sumathi, S., & Deepa, S. N., 2007. Introduction to fuzzy logic using MATLAB (Vol. 1). Berlin: Springer.
  • [12] Taskin, A., & Kumbasar, T., 2015. An open source Matlab/Simulink toolbox for interval type-2 fuzzy logic systems. In 2015 IEEE Symposium Series on Computational Intelligence, 1561-1568, IEEE.
  • [13]. Özkan, M. (2018). An Application for Individual Employee Performance Evaluation By Fuzzy Inference System. Cumhuriyet University Journal of Economics and Administrative Sciences, 19(2), 372-388.
  • [14]. Dhiman, N., & Sharma, M. 2020. Fuzzy logic inference system for identification and prevention of Coronavirus (COVID-19). International Journal of Innovative Technology and Exploring Engineering, 9(6).
  • [15]. Sharma, M. K., Dhiman, N., & Mishra, V. N. 2021. Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic. Applied Soft Computing, 105, 107285.
  • [16]. Castillo, O., & Melin, P. 2020. Forecasting of COVID-19 time series for countries in the world based on a hybrid approach combining the fractal dimension and fuzzy logic. Chaos, Solitons & Fractals, 140, 110242.
  • [17]. Marwaha J, Shah K. 2020. Safety & Preventive Measures for Dental Health Care Professionals on COVID-19. International Journal of Science and Healthcare Research. 5(2).
  • [18]. Lakha B., Goyal R., Singh R., 2009. Design and VLSI implementation of Fuzzy Logic Controller. International Journal of Computer and Network Security.
  • [19]. Sivanandam S.N., Sumathi S., Deepa S.N., 2007. Introduction to Fuzzy Logic Using Matlab, Springer, 95-101.
  • [20]. Wikipedia, 2019. Covid-19, Access Link : https://tr.wikipedia.org/wiki/COVID-19, Access Date : 20.08.2021.

Fuzzy Logic-Based Decision Support System for Covid-19 Emergency State Determination

Year 2021, Volume: 4 Issue: 2, 58 - 67, 31.08.2021

Abstract

The World Health Organization defined the COVID-19 outbreak as a global epidemic (pandemic) on March 11 due to the occurrence of COVID-19 cases in 113 countries outside China where the first epidemic started, and the spread and severity of the virus. The virus epidemic, which emerged in Wuhan, the capital of the Hubei region of China on 1 December 2019, has spread throughout the world.
The number of cases has exceeded 200 million and the number of deaths has exceeded 4 million. In this study, the symptoms and results of covid-19 were modeled with fuzzy logic and evaluated. In the model, the symptoms of the virus such as fever, dry cough, fatigue, loss of taste and smell, permanent pain in the chest, travel history, and sore throat were identified as input. The risk situation, quarantine situation, and isolation situation were determined as output, decision rules were created. These rules will make it easier to understand and use a model that cannot be built mathematically by building on natural languages and showing it with graphics as well as a rule table. With this study, it is predicted that it will be a model for decision-makers in the field of health.

References

  • [1] Republic of Turkey Ministry of Health Directorate General of Public Health, 2020. Covid-19 Scientific Advisory Board Study, Access Link : https://covid19.saglik.gov.tr/Eklenti/39551/0/covid-19rehberigenelbilgilerepidemiyolojivetanipdf.pdf.
  • [2]. Singh R., Avikal, S., 2020. COVID-19: A decision-making approach for prioritization of preventive activities, International Journal of Healthcare Management, 13:3, 257-262, DOI: 10.1080/20479700.2020.1782661.
  • [3]. World Health Organization (WHO), 2019. Coronavirus disease (COVID-19): How is transmitted?, Access Date: 17 August 2021.
  • [4]. Google News, 2019. Access Link : (https://news.google.com/covid19/map?hl=tr&mid=%2Fm%2F01znc_&gl=TR&ceid=TR%3Atr), Access Date: 17 August 2021
  • [5] Zhou Y, Yang Y, Huang J, Jiang S, Du L., 2019. Advances in MERS-CoV Vaccines and Therapeutics Based on the Receptor-Binding Domain. Viruses. Pp :11(1).
  • [6] Samaddar, S., Nargundkar, S., ve Daley, M., 2006. Inter-organizational information sharing: The role of supply network configuration and partner goal congruence, European Journal of Operational Research, 174(2), 744-765.
  • [7] Arji G, Ahmadi H, Nilashi M, Rashid T, Ahmed O, Aljojo N, Zainol A., 2019. Fuzzy logic approach for infectious disease diagnosis: A methodical evaluation, literature and classification. Biocybernetics and biomedical engineering, 39(4), 937–955.
  • [8] Adwibowo, A., 2020. Fuzzy logic assisted COVID 19 safety assessment of dental care, medRxiv.
  • [9] Kubat C., 2017. Matlab Artificial Intelligence and Engineering Applications, Third Edition, Abaküs Publications, 620-666.
  • [10] Bing W., Tingting C., Tsz Leung Y., Yang W., 2020. Fuzzy logic based dynamic decision-making system for intelligent navigation strategy within inland traffic separation schemes, Ocean Engineering, (Vol. 197:106909), doi.org/10.1016/j.oceaneng.2019.106909.
  • [11] Sivanandam, S. N., Sumathi, S., & Deepa, S. N., 2007. Introduction to fuzzy logic using MATLAB (Vol. 1). Berlin: Springer.
  • [12] Taskin, A., & Kumbasar, T., 2015. An open source Matlab/Simulink toolbox for interval type-2 fuzzy logic systems. In 2015 IEEE Symposium Series on Computational Intelligence, 1561-1568, IEEE.
  • [13]. Özkan, M. (2018). An Application for Individual Employee Performance Evaluation By Fuzzy Inference System. Cumhuriyet University Journal of Economics and Administrative Sciences, 19(2), 372-388.
  • [14]. Dhiman, N., & Sharma, M. 2020. Fuzzy logic inference system for identification and prevention of Coronavirus (COVID-19). International Journal of Innovative Technology and Exploring Engineering, 9(6).
  • [15]. Sharma, M. K., Dhiman, N., & Mishra, V. N. 2021. Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic. Applied Soft Computing, 105, 107285.
  • [16]. Castillo, O., & Melin, P. 2020. Forecasting of COVID-19 time series for countries in the world based on a hybrid approach combining the fractal dimension and fuzzy logic. Chaos, Solitons & Fractals, 140, 110242.
  • [17]. Marwaha J, Shah K. 2020. Safety & Preventive Measures for Dental Health Care Professionals on COVID-19. International Journal of Science and Healthcare Research. 5(2).
  • [18]. Lakha B., Goyal R., Singh R., 2009. Design and VLSI implementation of Fuzzy Logic Controller. International Journal of Computer and Network Security.
  • [19]. Sivanandam S.N., Sumathi S., Deepa S.N., 2007. Introduction to Fuzzy Logic Using Matlab, Springer, 95-101.
  • [20]. Wikipedia, 2019. Covid-19, Access Link : https://tr.wikipedia.org/wiki/COVID-19, Access Date : 20.08.2021.
There are 20 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Original Research Articles
Authors

İlhan Uysal 0000-0002-6091-9110

Utku Köse 0000-0002-9652-6415

Publication Date August 31, 2021
Acceptance Date August 25, 2021
Published in Issue Year 2021 Volume: 4 Issue: 2

Cite

APA Uysal, İ., & Köse, U. (2021). Fuzzy Logic-Based Decision Support System for Covid-19 Emergency State Determination. Scientific Journal of Mehmet Akif Ersoy University, 4(2), 58-67.