Journal of Computer and Communications

Volume 8, Issue 12 (December 2020)

ISSN Print: 2327-5219   ISSN Online: 2327-5227

Google-based Impact Factor: 1.12  Citations  

A Prediction Method Based on Improved Echo State Network for COVID-19 Nonlinear Time Series

HTML  XML Download Download as PDF (Size: 1012KB)  PP. 113-122  
DOI: 10.4236/jcc.2020.812011    378 Downloads   936 Views  Citations

ABSTRACT

This paper proposes a prediction method based on improved Echo State Network for COVID-19 nonlinear time series, which improves the Echo State Network from the reservoir topology and the output weight matrix, and adopt the ABC (Artificial Bee Colony) algorithm based on crossover and crowding strategy to optimize the parameters. Finally, the proposed method is simulated and the results show that it has stronger prediction ability for COVID-19 nonlinear time series.

Share and Cite:

Liu, B. , Chen, W. , Chen, Y. , Sun, P. , Jin, H. and Chen, H. (2020) A Prediction Method Based on Improved Echo State Network for COVID-19 Nonlinear Time Series. Journal of Computer and Communications, 8, 113-122. doi: 10.4236/jcc.2020.812011.

Cited by

No relevant information.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.