Artificial Intelligence based Forecasting Techniques for the Covid-19 pandemic

Srinivas, Kandala Kalyana and Vangara, Paniteja and Thiparapu, Radha and Sravanth Kumar, R and Bhagavathi, Kandala Aditya (2022) Artificial Intelligence based Forecasting Techniques for the Covid-19 pandemic. In: 2022 International Mobile and Embedded Technology Conference, MECON 2022, 10 March 2022 through 11 March 2022, Noida.

[img] Text
2022_International_Mobile_and_Embedded_Technology_Conference.pdf - Published Version
Restricted to Registered users only

Download (366kB) | Request a copy


The burial of bodies became a trend in the cause of ongoing pending (Novel Coronavirus), more than50 a million people all over the globe are adversely affected, hence the analysis and forecasting techniques are necessary to regain the human livelihood. The enlargement of technologies such as Artificial Intelligence, Machine Learning, Deep Learning, are en route into all the living aspects. Hence by using AI, ML, DL, Advanced technologies and existing models ARIMA, PROPHET, SVM, RNN, Faster Mask R-CNN, RESNET-50, and other techniques such as logarithmic scaling and exponential smoothing so on, the spread of VIRUS, the effect of countries economic growth, confirmed cases, fatality rate, recoveries are predicted to overcome the life threat due to SARS. Such that different predictive techniques are used to forecast. The advancement in the past algorithms to acquire accurate results are been introduced and described. © 2022 IEEE.

[error in script]
IITH Creators:
IITH CreatorsORCiD
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: ARIMA; Bayesian adaptive learning; etc; LSTM; Resnet-101; RNN; SOMFTS
Subjects: Others > Medicine
Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 20 Jul 2022 11:14
Last Modified: 20 Jul 2022 11:14
Publisher URL:
Related URLs:

    Actions (login required)

    View Item View Item
    Statistics for RAIITH ePrint 9816 Statistics for this ePrint Item