Optimization Method for Forecasting Confirmed Cases of COVID-19 in China
Wuhan University · State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing · +3 more institutions
Abstract
In December 2019, a novel coronavirus, called COVID-19, was discovered in Wuhan, China, and has spread to different cities in China as well as to 24 other countries. The number of confirmed cases is increasing daily and reached 34,598 on 8 February 2020. In the current study, we present a new forecasting model to estimate and forecast the number of confirmed cases of COVID-19 in the upcoming ten days based on the previously confirmed cases recorded in China. The proposed model is an improved adaptive neuro-fuzzy inference system (ANFIS) using an enhanced flower pollination algorithm (FPA) by using the salp swarm algorithm (SSA). In general, SSA is employed to improve FPA to avoid its drawbacks (i.e., getting…
Citation impact
- FWCI
- 15.05
- Percentile
- 100%
- References
- 66
Authors
4- MAMohammed A. A. Al‐qaness
Wuhan University, State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
- AAAhmed A. Ewees
Damietta University, University of Bisha
- HFHong FanCorresponding
Wuhan University, State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
- MAMohamed Abd Elaziz
Zagazig University
Topics & keywords
- Adaptive neuro fuzzy inference system
- Mean absolute percentage error
- Mean squared error
- Coronavirus disease 2019 (COVID-19)
- Statistics
- Inference system
- China
- Medicine