A COVID-19 forecasting system using adaptive neuro-fuzzy inference
Kim Tien Ly
Finance Research Letters, 2021, vol. 41, issue C
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.
Keywords: ANFIS; Time series; Forecasting system; Coronavirus; Contagion effect (search for similar items in EconPapers)
JEL-codes: C53 C67 G15 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:41:y:2021:i:c:s1544612320316585
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