Abstract
Coronavirus Disease (COVID-19) was declared as a pandemic. Recently, this pandemic is considered one of the main points of research. Many researchers introduce a lot of methods to predict the outbreaks of a dangerous pandemic. This paper will introduce a new technique to predict the daily reports for the next months based on one of the modern optimization techniques called Chaotic Fruit Fly. We will be applied to those techniques. Then we will follow the learning transfer function “sigmoid function”. Moreover, we will compare our algorithm with the previous ones of predictions. The method which is introduced in this paper is much more accurate than the other methods. The method has been applied to the Egyptian report of daily and death cases. The result shows the accuracy of the prediction for the next three months. Further, the results show the effect of the algorithm accuracy. In this paper, we compare accuracy with the other predictions applied to COVID-19 cases.
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Aly, R.H.M., Rahouma, K.H. (2021). COVID-19 Outbreak Learning Prediction Based on Swarm Intelligence Model “Chaotic Fruit Fly Algorithm Followed by Activation Function”. In: Hassanien, AE., Chang, KC., Mincong, T. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2021. Advances in Intelligent Systems and Computing, vol 1339. Springer, Cham. https://doi.org/10.1007/978-3-030-69717-4_6
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DOI: https://doi.org/10.1007/978-3-030-69717-4_6
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