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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM11935
Volume:
6 |
3 |
Mar 2022
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Machine learning (ML) based on predicting and predicting algorithms and proving their value and importance in statistical prediction problems to improve the accuracy and results of a given problem. ML models have long been used in many application domains that required the identification and prediction of a number of information items. A few predictive methods are often used to manage prediction problems. This study will demonstrate the ability of machine learning models to predict the number of future patients with COVID-19, currently considered a potential threat to humanity. in particular, the implementation of the Long Short Term Networks algorithm is recommended to extend the efficiency of the currently available models. Three different types of speculation are made by each model, such as the number of newly infected cases, the death rate, and the recovery rate over the next 10 days.
KEYWORDS
Publication Date
3/22/2022
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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