id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-282977-kmj8hj78	Babbar, S.	Battle with COVID-19 Under Partial to Zero Lockdowns in India	2020-07-04		.txt	text/plain	6077	353	64	Instead of fixing parameters of the standard SEIR model before simulation, we propose to learn them from the real data set consisting of progression of Corona spread in India. The learning of model is carefully designed by understanding that available data set consist of records of cases under full, partial to zero lockdown phases in India. These two predictions presented in this work provide awareness among citizens of India on importance of control measures such as full, partial and zero lockdown and the spread of Corona disease infection rate. The key motivation to integrate two methods for the predictive task is to use benefits of SEIR model by making its key parameters learn using historical data of confirmed cases under full and partial to zero lockdowns in India. Figures 5 and 6 represents fitting of learned model over actual new cases of Coronavirus data set of India and Delhi respectively.	./cache/cord-282977-kmj8hj78.txt	./txt/cord-282977-kmj8hj78.txt