Amjed Basil Abdulkareem1, Nor Samsiah Sani1,*, Shahnorbanun Sahran1, Zaid Abdi Alkareem Alyessari1, Afzan Adam1, Abdul Hadi Abd Rahman1, Abdulkarem Basil Abdulkarem2
Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 305-320, 2021, DOI:10.32604/iasc.2021.015413
- 01 April 2021
Abstract The coronavirus disease 2019 (COVID-19) has infected more than 50 million people in more than 100 countries, resulting in a major global impact. Many studies on the potential roles of environmental factors in the transmission of the novel COVID-19 have been published. However, the impact of environmental factors on COVID-19 remains controversial. Machine learning techniques have been used effectively in combating the COVID-19 epidemic. However, researches related to machine learning on weather conditions in spreading COVID-19 is generally lacking. Therefore, in this study, three machine learning models (Convolution Neural Network (CNN), ADtree Classifier and BayesNet)… More >