The prediction analysis of Covid-19 using enhanced deep learning network and improvised optimization algorithms.
In: AIP Conference Proceedings, Jg. 2930 (2023-10-24), Heft 1, S. 1-12
Konferenz
Zugriff:
To predict the effects, risks, and parameters of current pandemic the Artificial Intelligence methods have been used. The predictions should be supportive to prevent and control of this deadly disease. However there exist challenges in imposing AI technique because of their uncertainty and lesser volume of data. Used of neural network based Long Short-Term Memory (LSTM) for risk prediction of nearly 170 countries. For optimizing the prediction value Bayesian optimization technique has used. To take preventive steps this current study exhibiting a tool for predicting the long-duration pandemic. For prediction, the weather and trend data combined in this study. This model used soft computing and machine learning techniques for covid-19 outbreak prediction. Several issues such as uncertainty, essential data lacking, lack of robustness and required generalization deficient have been trying to overcome by this study. The two machine learning models have used in this work (fuzzy inference system and multi layered p erceptron model with adaptive network). Despite the behavior variations seen in covid-19 from various countries and the COVID-19 difficult nature this study termed as an effective tool for prediction. Still need advancement in techniques to predict the lo ng-term duration and required generalization ability. However, for long term prediction various other deep learning and machine learning techniques is considered. In addition to that the differences among the outbreak seen in other countries required global model comprised with generalization ability. Also, the most complex prediction stated is to evaluate the extreme number of covid-19 infected patients and at the same time evaluation deaths / infected patients is essential. Hence mortality rate in prediction analysis also significant in order to arranging the intensive care units. For the countrywide nations to plan new facilities among the outbreak the enhanced kind of modelling is essential. [ABSTRACT FROM AUTHOR]
Titel: |
The prediction analysis of Covid-19 using enhanced deep learning network and improvised optimization algorithms.
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Autor/in / Beteiligte Person: | Yenurkar, Ganesh K. ; Mal, Sandip |
Zeitschrift: | AIP Conference Proceedings, Jg. 2930 (2023-10-24), Heft 1, S. 1-12 |
Quelle: | 2023, Vol. 2930 Issue 1, p1-12. 12p.; Jg. 2930 (2023-10-24) 1, S. 1-12 |
Veröffentlichung: | 2023 |
Medientyp: | Konferenz |
ISSN: | 0094-243X (print) |
DOI: | 10.1063/5.0175844 |
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