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Interval type-2 fuzzy computational model for real time Kalman filtering and forecasting of the dynamic spreading behavior of novel Coronavirus 2019.
Dos Santos Gomes, Daiana Caroline; de Oliveira Serra, Ginalber Luiz.
Afiliação
  • Dos Santos Gomes DC; Federal University of Maranhão, São Luís-Maranhão, Brazil.
  • de Oliveira Serra GL; Federal Institute of Education, Science and Technology of Maranhão, São Luís-Maranhão, Brazil. Electronic address: ginalber@ifma.edu.br.
ISA Trans ; 124: 57-68, 2022 May.
Article em En | MEDLINE | ID: mdl-35450726
This paper presents a computational model based on interval type-2 fuzzy systems for analysis and forecasting of COVID-19 dynamic spreading behavior. The proposed methodology is related to interval type-2 fuzzy Kalman filters design from experimental data of daily deaths reports. Initially, a recursive spectral decomposition is performed on the experimental dataset to extract relevant unobservable components for parametric estimation of the interval type-2 fuzzy Kalman filter. The antecedent propositions of fuzzy rules are obtained by formulating a type-2 fuzzy clustering algorithm. The state space submodels and the interval Kalman gains in consequent propositions of fuzzy rules are recursively updated by a proposed interval type-2 fuzzy Observer/Kalman Filter Identification (OKID) algorithm, taking into account the unobservable components obtained by recursive spectral decomposition of epidemiological experimental data of COVID-19. For validation purposes, through a comparative analysis with relevant references of literature, the proposed methodology is evaluated from the adaptive tracking and forecasting of COVID-19 dynamic spreading behavior, in Brazil, with the better results for RMSE of 1.24×10-5, MAE of 2.62×10-6, R2 of 0.99976, and MAPE of 6.33×10-6.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Lógica Fuzzy / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: ISA Trans Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Brasil País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Lógica Fuzzy / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: ISA Trans Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Brasil País de publicação: Estados Unidos