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Applying Smart Restrictions In The Face of Epidemic Diseases (Case study of COVID-19)
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Mohammad Reza Malek *   , Mohammad Khalili , Ghobad Moradi |
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Abstract: (121 Views) |
The spread of Covid-19 has become one of the most important challenges in the world. This disease spread rapidly in the world and involved all countries. Most countries tried to deal with it with non-pharmacological interventions, including the imposition of coronavirus restrictions. Predicting this disease is one of the basic ways to deal with it. By predicting the condition of this disease, control measures to deal with this disease can be better managed. Also, in various studies, factors affecting the spread of this disease have been investigated. Paying attention to these factors can play a significant role in improving the management of this disease. Smart application of restrictions for urban management can prevent social, economic, and environmental losses in addition to controlling the spread of disease. Therefore, a two-stage model was designed for the intelligent application of restrictions. In the first stage, the adaptive neural fuzzy system was used to predict the disease, and in the second stage, the fuzzy expert system was used to apply the influence of the influencing factors on the disease outbreak. Finally, the created vulnerability map was used to apply restrictions. For the first step, the results of the comparison of the root mean square error for three clustering methods showed that the combined clustering with a value of 0.53294 works better than the two fuzzy and reduced clustering methods. In the second stage, factors of population density, elderly population density, spatial displacement, distance from busy places, access to medical resources, and cases of this disease were used and a vulnerability map was calculated and produced for the considered period. This map was used to decide the smart application of restrictions for decision-making bodies, and the map of smart application of restrictions was produced for four education and training bodies, the municipality, the health organization, and the governor's office. The results show that despite the application of complete measures for all works on December 30, 2019, in Qom city, some areas of dangerous situation were not areas without the need to apply restrictions in these areas. In education, there was no need to close 58% of the province's schools in this history, and in the municipality, there was no need to close 40% of the parks and gardens, and they could continue their activities by following health protocols.
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Article number: 5 |
| Keywords: Epidemic, Covid-19-, Smart job restrictions, Adaptive neural fuzzy system -ANFIS, Fuzzy expert system |
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Full-Text [PDF 1202 kb]
(79 Downloads)
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Type of Study: Research |
Subject:
GIS
Received: 2024/02/7
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