Titlebook: Artificial Intelligence for COVID-19; Diego Oliva,Said Ali Hassan,Ali Mohamed Book 2021 The Editor(s) (if applicable) and The Author(s), u

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Nonparametric Tests for Comparing COVID-19 Machine Learning Forecasting Models,e statistical sense differ little from each other (homogeneous) and therefore such models can be considered equivalent. The chapter describes an effective nonparametric tests both traditional and new for comparing the results of time series prediction, which makes it possible to assess their homogen

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Optimum Scheduling of the Disinfection Process for COVID-19 in Public Places with a Case Study froms solved using a novel Discrete Binary Gaining-Sharing knowledge-based optimization algorithm (DBGSK). The results of this study show that the novel optimization algorithm can efficiently solve the proposed Problem.

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Predicating COVID19 Epidemic in Nepal Using the SIR Model,deaths per day. . This simulation type can help improve comprehension of disease spread dynamics and provide control measures for an epidemic outbreak. The suggestion that authorities need to implement a strict containment strategy over a long period to control disease spreading on the community and