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Data mining and exploratory data analysis of Covid-19 virus diffusion in the world

عنوان مقاله: Data mining and exploratory data analysis of Covid-19 virus diffusion in the world
شناسه ملی مقاله: RMIECONF04_003
منتشر شده در چهارمین کنفرانس بین المللی پیشرفت های اخیر در مدیریت و مهندسی صنایع در سال 1399
مشخصات نویسندگان مقاله:

Reza Parvizi - Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Iran

خلاصه مقاله:
In late December 2019, a new virus, called Covid-19, began to spread from China and soon spread around the world. The Covid-19 epidemic poses major health threats to global public health. The disease is spreading all over the world, causing many people to suffer, and endangering public health everywhere. As long as there is no fundamental solution to control the corona virus, health protocols can prevent the virus from spreading more widely. By analyzing the available data from databases registered in different parts of the world, appropriate patterns of the virus propagation process can be obtained. Covid-19 control managers can develop better health protocols to prevent further spread of the Covid-19 by being aware of the diffusion of the virus in different areas. Data mining and data analyzing is the best method to predict how this virus can spread more in the world. In this study, using the database of the World Health Organization, data from around the country world have been analyzing with exploratory data analysis approach to examine the rate of progression, diffusion and rate of death due to this virus.

کلمات کلیدی:
COVID-19, Data mining, Exploratory data analysis, World Health Organization

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1118369/