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Academic Journal of Applied Mathematical Sciences

Online ISSN: 2415-2188
Print ISSN: 2415-5225

Quarterly Published (4 Issues Per Year)

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Volume 6 Number 4 April 2020

Predicting COVID-19 Cases using Some Statistical Models: An Application to the Cases Reported in China Italy and USA

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Authors: Mostafa Salaheldin Abdelsalam Abotaleb
Pages: 32-40
DOI: doi.org/10.32861/ajams.64.32.40
Abstract

Today, the new coronavirus disease (COVID-19) is a global epidemic that spreads rapidly among individuals in most countries around the world and, therefore, becomes the greatest worldwide threat. The aim of this study is to find the best predictive models for the confirmation of daily situations in countries with a large number of confirmed cases. The study was conducted on the countries that recorded the highest infection rate, namely China, Italy and the United States of America. The second goal is using predictive models to get more prepared in terms of health care systems. In this study, predictions were made through statistical prediction models using the ARIMA and exponential growth model. The results indicate that the exponential growth model is better than ARIMA models for forecasting the COVID-19 cases.

Finite-Time Stabilization of Switched Systems with Time-Varying Delay

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Authors: Mengxiao Deng ; Yali Dong
Pages: 24-31
DOI: doi.org/10.32861/ajams.64.24.31
Abstract

This paper studies the problem of finite-time stabilization of a class of switched linear time-varying delay systems. An event-triggered sampling mechanism and an event-triggered state feedback control are proposed. Based on Lyapunov-like function method, linear matrix inequality technique and averaged dwell time method, sufficient conditions for switched delay systems under event-triggered state feedback control are given to ensure the finite-time stabilization of the switched delay systems. Finally, a numerical example is given to verify the validity of the proposed results.