Application of a Hybrid Method Combining Grey Model and Back Propagation Artificial Neural Networks to Forecast Hepatitis B in China
Joint Authors
Gan, Ruijing
Chen, Xiaojun
Yan, Yu
Huang, Daizheng
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-02-26
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Accurate incidence forecasting of infectious disease provides potentially valuable insights in its own right.
It is critical for early prevention and may contribute to health services management and syndrome surveillance.
This study investigates the use of a hybrid algorithm combining grey model (GM) and back propagation artificial neural networks (BP-ANN) to forecast hepatitis B in China based on the yearly numbers of hepatitis B and to evaluate the method’s feasibility.
The results showed that the proposal method has advantages over GM (1, 1) and GM (2, 1) in all the evaluation indexes.
American Psychological Association (APA)
Gan, Ruijing& Chen, Xiaojun& Yan, Yu& Huang, Daizheng. 2015. Application of a Hybrid Method Combining Grey Model and Back Propagation Artificial Neural Networks to Forecast Hepatitis B in China. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1057865
Modern Language Association (MLA)
Gan, Ruijing…[et al.]. Application of a Hybrid Method Combining Grey Model and Back Propagation Artificial Neural Networks to Forecast Hepatitis B in China. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-7.
https://search.emarefa.net/detail/BIM-1057865
American Medical Association (AMA)
Gan, Ruijing& Chen, Xiaojun& Yan, Yu& Huang, Daizheng. Application of a Hybrid Method Combining Grey Model and Back Propagation Artificial Neural Networks to Forecast Hepatitis B in China. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1057865
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057865
