使用监督学习技术的封锁和封锁后对印度covid - 19病例的影响

2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Pub Date : 2020-10-28 DOI:10.1109/UEMCON51285.2020.9298183

Narayana Darapaneni, Amol Kobal, Rohit Chaoji, R. Tiwari, S. Saurav, A. Paduri

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引用次数: 0

摘要

冠状病毒(或Covid-19)的爆发是一场重大的全球大流行，已经感染了全球数百万人。印度是受此次大流行影响最严重的国家之一，截至2020年9月10日，有450多万人感染了该病毒。印度政府采取了各种方法来控制疫情，包括封锁等非医疗干预措施。本文件详细分析了封锁对遏制Covid-19在印度传播的影响。这项工作包括应用不同的统计技术来了解印度各地实施封锁的各个阶段的病毒进展情况。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Effects of Lockdown and Post Lockdown on Covid19 cases across India using Supervised Learning Techniques

The Coronavirus (or Covid-19) outbreak is a major global pandemic, which has infected millions of people across the world. India has been one of the worst hit country by this pandemic with over 4.5 million people affected by the virus as of 10th Sept 2020. The governments in India took various methods to contain the outbreak including non-medical interventions like lockdown. This document provides detailed analysis of effect of lockdown in containing the spread of Covid-19 in India. This work comprises of applying different statistical techniques to comprehend the Virus progression during various phases of lockdown implemented across India.

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2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)

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