ABSTRACT
As perceived at mostly countries, after the 3th or 4th wave of Covid-19 pandemic, its potential end might be coming. In contrast to previous waves, the last one exhibits different characteristics such as a highly exponential behavior or also a sharped Gauss behavior as seen at the huge number of infections at America and Europe. In this paper is proposed the idea that the whole pandemic is clearly composed by a sinusoid and Gaussian functions. This claim is based at the world-wide data that exhbits a similar shape with the proposed scheme at this study. Thus, the pandemic can also be seen as a signal-noise being the Omicron variant the signal whereas the previous mutations can be seen as their background events or noise. © 2022 IEEE.
ABSTRACT
In late 2019, pneumonia epidemics were recorded in Wuhan, China, affecting a large number of individuals. A novel SARS virus was found after a careful investigation of samples from SARS patients. The virus was given the name CORONA because of its coronavirus origin, which was then shortened to COVID-19, which stands for CORONA VIRUS 2019. The World Health Organization declared a pandemic on March 11, 2020. The human brain served as the foundation for civilisation. Neural networks were designed to mimic the human mind's working style in order to profit from their way of thinking. The network of neurons performs similarly to a human neuron. As a result, RBF neural networks have been used to link diagnosis with symptoms because the base-based system is reconciled with the knowledge-based system, which represents symptoms related to the diagnosed disease, and the system becomes suitable for correct disease diagnosis after network training. The current study has two main stages: neuron training, which entails entering the system's parameters and generating random weights ranging from 0 to 1 for each of these parameters, and then applying the RBF neural network function to it and comparing the results with those obtained through COVID-19 health centers. © 2022 IEEE.