Forecasting COVID-19 Patients & Power Demand in Bangladesh

dc.contributor.author	Azad, Saad Ebna
dc.contributor.author	Anwar, Atif Mohd.
dc.contributor.author	Saharear, Fahim Md.
dc.date.accessioned	2022-04-20T06:28:43Z
dc.date.available	2022-04-20T06:28:43Z
dc.date.issued	2021-03-30
dc.identifier.uri	http://hdl.handle.net/123456789/1365
dc.description	Supervised by Prof. Dr. Khondokar Habibul Kabir, Department of Electrical and Electronics Engineering(EEE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.description.abstract	This research gives a better understanding & analysis of the global pandemic situation of covid-19 in Bangladesh. Using machine learning this model accurately forecasts new cases, deaths & recoveries. Then it forecasts the necessary hospital seats & power demands for those seats. This hopefully will provide a better support for the struggling power sector of developing countries like Bangladesh. This will also help to prepare other countries who are struggling for such epidemic situations in the future.	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Electrical and Electronic Engineering, Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.subject	Machine learning, COVID-19, ARIMA, CSSE, SVM, RMSE	en_US
dc.title	Forecasting COVID-19 Patients & Power Demand in Bangladesh	en_US
dc.type	Thesis	en_US