Introduction: At the end of 2019, contamination caused by an unknown virus affected the population of Wuhan, China. The virus, known as SARS-CoV-2, was found to cause flulike symptoms, such as fever, cough, among others. Objective: using the fuzzy logic method graphically demonstrated the Risk of Collapse of the Health System, with the availability of beds /equipment to increase the number of infected, from the Sars-CoV-2 pandemic. Methods: Modeled a fuzzy system with a Mamdani model, later defined the physical variables of entry (Number of infected people and number of beds/equipment available) and output (Risk of collapse of the health system), then inserted the nine rules and the pertinence functions in the trapezoidal and triangular type graph, generating from this information a three-dimensional graph with the results. Results: From the threedimensional graph, it can be seen that the results were consistent and demonstrate that countries must prevent the number of infected people from increasing, because when this situation occurs, the risk of collapse of the health system is high due to the unavailability of beds /equipment, in addition, this modeling of fuzzy logic along with the generated three-dimensional graph can be used to demonstrate a health crisis in countries. Conclusion: Concluded that the fuzzy logic technique allows many realistic predictions of possible crises and collapses of the health system, but to obtain good results in it, having the knowledge of what is expected will generate the necessary notion to make the insertion of information accurately in the software.
At the end of 2019 a respiratory syndrome hit the population of China. Studies have found that this contamination was caused by the SARS-CoV-2 virus. By 2020, the coronavirus contamination spread around the world, generating a pandemic that has impacted the health of millions of people. Looking for methods to understand the spread of the pandemic is fundamental to define prevention and containment measures, the use of computer software provide a view of the evolution of contamination. Fuzzy logic is a logical technique based on Fuzzy set theory and, using this theory, it is possible to deal with uncertainties, approximate reasoning, vague and ambiguous terms, which classical logic does not allow. In order to model the system, you must define the input and output variables, write the rule sets and insert the pertinence functions with the graph type to be used. For this work, the modeling was performed having two variables in the input and each variable presented three pertinence functions, and one output variable that also had three pertinence functions and nine rules. The results obtained were coherent and demonstrated graphically what would happen to a susceptible group if they were exposed without any form of isolation or protection.
Análise de mínima fluidização de leito fluidizado em 3D via CFD para o material orgânico café Minimum fluidization analysis of 3D fluidized bed through CFD for coffee organic material
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