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Forecasting COVID- 19 cases using Statistical Models and Ontology-based Semantic Modelling: A real time data analytics approach. (arXiv:2206.02795v1 [q-bio.PE])
cs.LG updates on arXiv.org arxiv.org
SARS-COV-19 is the most prominent issue which many countries face today. The
frequent changes in infections, recovered and deaths represents the dynamic
nature of this pandemic. It is very crucial to predict the spreading rate of
this virus for accurate decision making against fighting with the situation of
getting infected through the virus, tracking and controlling the virus
transmission in the community. We develop a prediction model using statistical
time series models such as SARIMA and FBProphet to monitor the …
analytics arxiv bio cases covid data data analytics forecasting modelling ontology real time data semantic statistical time