Prediction of the effects of environmental factors towards COVID-19 outbreak using AI-based models

<p>The need for elucidating the effects of environmental factors in determination novel corona virus (COVID-19) is very vital. This study a methodological to compare three different test models (1. Artificial neural networks (ANN), 2. Adaptive neuro fuzzy inference system (ANFIS), 3. A linear classical model (MLR)) used determine relationship between COVID-19 spread and (temperature, humidity wind). These data were obtained from studies (Pirouz, Haghshenas, & Piro, 2020) with confirmed patients Wuhan, China, using temperature, wind as independent variables. The measured predicted results checked based on performance indices; Root mean square error (RMSE), coefficient (R2) correlation (R). showed that ANFIS ANN are more promising over MLR having an average R-values 0.90 both calibration verification stages. findings indicated outperformed ANN. In addition, their skills boosted up 25% 9% respectively prediction cases Wuhan city China. Overall, depict reliability ability AI-based (ANFIS ANN) simulation various </p>