- author = "Musa Khan and Gul Muhammad Khan",
- title = "{COVID-19} Spread Prediction and Its Impact on the Stock market price",
- booktitle = "2022 2nd International Conference on Artificial Intelligence (ICAI)",
- year = "2022",
- pages = "140--146",
- month = "30-31 " # mar,
- address = "Islamabad, Pakistan",
- keywords = "genetic algorithms, genetic programming, Cartesian genetic programming, Covid-19, Time series forecasting, CGPANN, Neuroevolution, Stock Market index",
- isbn13 = "978-1-6654-6897-8",
-
DOI = "
doi:10.1109/ICAI55435.2022.9773481",
- size = "7 pages",
- abstract = "Predicting the Covid-19 spread and its impact on the stock market is an important research challenge these days. In order to obtain the best forecasting model, we have exploited neuro-evolutionary technique Cartesian genetic programming evolved artificial neural network (CGPANN) based solution to predict the future cases of COVID-19 up to 6-days in advance. This helps authorities and paramedical staff to take precautionary measures on time which helps in counteracting the spreading of the virus. The rising number of COVID cases has caused a significant impact on the stock market. CGPANN being the best performer for the time series prediction model seems ideal for the case under consideration. The proposed model achieved an accuracy as high as 98 percent predicting COVID-19 cases for the next six days. When compared with other contemporary models CGPANN seems to perform well ahead in terms of accuracy.",
-
notes = "Also known as \cite{9773481}
p146 'we test our proposed CGPANN model on 30 other Asian countries' 'Nvidia GeForce MX150'",
