A COVID-19 forecasting system using adaptive neuro-fuzzy inference

This article proposes an Adaptive Neuro-Fuzzy Inference System (ANFIS) to forecast the number of COVID-19 cases in the United Kingdom. With the combination of artificial neural network and fuzzy logic structure, the model is trained based on collected data. The study examines various factors of ANFI...

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Detalles Bibliográficos
Autor principal: Ly, Kim Tien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8191513/
https://www.ncbi.nlm.nih.gov/pubmed/34131413
http://dx.doi.org/10.1016/j.frl.2020.101844
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author Ly, Kim Tien
author_facet Ly, Kim Tien
author_sort Ly, Kim Tien
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description This article proposes an Adaptive Neuro-Fuzzy Inference System (ANFIS) to forecast the number of COVID-19 cases in the United Kingdom. With the combination of artificial neural network and fuzzy logic structure, the model is trained based on collected data. The study examines various factors of ANFIS to come up with an effective time series prediction model. The result indicates that Spain and Italy data can strengthen the predictive power of COVID-19 cases in the UK. It is suggested that the policymakers should adopt Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict contagion effect during the COVID-19 pandemic.
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spelling pubmed-81915132021-06-11 A COVID-19 forecasting system using adaptive neuro-fuzzy inference Ly, Kim Tien Financ Res Lett Article This article proposes an Adaptive Neuro-Fuzzy Inference System (ANFIS) to forecast the number of COVID-19 cases in the United Kingdom. With the combination of artificial neural network and fuzzy logic structure, the model is trained based on collected data. The study examines various factors of ANFIS to come up with an effective time series prediction model. The result indicates that Spain and Italy data can strengthen the predictive power of COVID-19 cases in the UK. It is suggested that the policymakers should adopt Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict contagion effect during the COVID-19 pandemic. Elsevier Inc. 2021-07 2020-11-12 /pmc/articles/PMC8191513/ /pubmed/34131413 http://dx.doi.org/10.1016/j.frl.2020.101844 Text en © 2020 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Ly, Kim Tien
A COVID-19 forecasting system using adaptive neuro-fuzzy inference
title A COVID-19 forecasting system using adaptive neuro-fuzzy inference
title_full A COVID-19 forecasting system using adaptive neuro-fuzzy inference
title_fullStr A COVID-19 forecasting system using adaptive neuro-fuzzy inference
title_full_unstemmed A COVID-19 forecasting system using adaptive neuro-fuzzy inference
title_short A COVID-19 forecasting system using adaptive neuro-fuzzy inference
title_sort covid-19 forecasting system using adaptive neuro-fuzzy inference
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8191513/
https://www.ncbi.nlm.nih.gov/pubmed/34131413
http://dx.doi.org/10.1016/j.frl.2020.101844
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