Intelligent Health Care and Diseases Management System: Multi-Day-Ahead Predictions of COVID-19
Mathematics, ISSN: 2227-7390, Vol: 11, Issue: 4
2023
- 1Citations
- 89Usage
- 24Captures
- 2Mentions
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations1
- Citation Indexes1
- Usage89
- Downloads71
- Abstract Views18
- Captures24
- Readers24
- 24
- Mentions2
- Blog Mentions1
- Blog1
- News Mentions1
- News1
Most Recent News
New Study Findings from Zayed University Illuminate Research in COVID-19 (Intelligent Health Care and Diseases Management System: Multi-Day-Ahead Predictions of COVID-19)
2023 MAR 08 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx COVID-19 Daily -- Current study results on COVID-19 have been published. According
Article Description
The rapidly growing number of COVID-19 infected and death cases has had a catastrophic worldwide impact. As a case study, the total number of death cases in Algeria is over two thousand people (increased with time), which drives us to search its possible trend for early warning and control. In this paper, the proposed model for making a time-series forecast for daily and total infected cases, death cases, and recovered cases for the countrywide Algeria COVID-19 dataset is a two-layer dropout gated recurrent unit (TDGRU). Four performance parameters were used to assess the model’s performance: mean absolute error (MAE), root mean squared error (RMSE), R (Formula presented.), and mean absolute percentage error (MAPE). The results generated with TDGRU are compared with actual numbers as well as predictions with conventional time-series techniques, such as autoregressive integrated moving average (ARIMA), machine learning model of linear regression (LR), and the time series-based deep learning method of long short-term memory (LSTM). The experiment results on different time horizons show that the TDGRU model outperforms the other forecasting methods that deliver correct predictions with lower prediction errors. Furthermore, since this TDGRU is based on a relatively simpler architecture than the LSTM, in comparison to LSTM-based models, it features a significantly reduced number of parameters, a shorter training period, a lower memory storage need, and a more straightforward hardware implementation.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85148938964&origin=inward; http://dx.doi.org/10.3390/math11041051; https://www.mdpi.com/2227-7390/11/4/1051; https://zuscholars.zu.ac.ae/works/5732; https://zuscholars.zu.ac.ae/cgi/viewcontent.cgi?article=6764&context=works; https://dx.doi.org/10.3390/math11041051
MDPI AG
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know