Your browser doesn't support javascript.
An Empirical Mode Decomposition Fuzzy Forecast Model for COVID-19.
Chen, Bo-Lun; Shen, Yi-Yun; Zhu, Guo-Chang; Yu, Yong-Tao; Ji, Min.
  • Chen BL; Department of Computer Science, Huaiyin Institute of Technology, Huaiyin, 223003 Jiangsu China.
  • Shen YY; Institute of Informatics, University of Zurich, 8050 Zurich, Switzerland.
  • Zhu GC; Department of Computer Science, Huaiyin Institute of Technology, Huaiyin, 223003 Jiangsu China.
  • Yu YT; Department of Computer Science, Huaiyin Institute of Technology, Huaiyin, 223003 Jiangsu China.
  • Ji M; Department of Computer Science, Huaiyin Institute of Technology, Huaiyin, 223003 Jiangsu China.
Neural Process Lett ; : 1-22, 2022 Apr 25.
Article in English | MEDLINE | ID: covidwho-1942453
ABSTRACT
At present, the Corona Virus Disease 2019 (COVID-19) is ravaging the world, bringing great impact on people's life safety and health as well as the healthy development of economy and society, so the research on the prediction of the development trend of the epidemic is crucial. In this paper, we focus on the prevention and control of epidemic using the relevant technologies in the field of artificial intelligence and signal analysis. With the unknown principle of epidemic transmission, we first smooth out the complex and variable epidemic data through the empirical mode decomposition model to obtain the change trends of epidemic data at different time scales. On this basis, the change trends under different time scales are trained using an extreme learning machine to obtain the corresponding prediction values, and finally the epidemic prediction results are obtained by fitting through Adaptive Network-based Fuzzy Inference System. The experimental results show that the algorithm has good learning ability, especially in the prediction of time-series sequences can guarantee the accuracy rate while having low time complexity. Therefore, this paper not only plays a theoretical support for epidemic prevention and control, but also plays an important role in the construction of public emergency health system in the long run.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: Neural Process Lett Year: 2022 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: Neural Process Lett Year: 2022 Document Type: Article