Comparisons of forecasting for hepatitis in Guangxi Province, China by using three neural networks models

Ruijing Gan; Ni Chen; Daizheng Huang

doi:10.7717/peerj.2684

Comparisons of forecasting for hepatitis in Guangxi Province, China by using three neural networks models

PeerJ. 2016 Nov 8:4:e2684. doi: 10.7717/peerj.2684. eCollection 2016.

Authors

Ruijing Gan¹, Ni Chen¹, Daizheng Huang¹

Affiliation

¹ School of Preclinical Medicine, Guangxi Medical University , Nanning, Guangxi , China.

Abstract

This study compares and evaluates the prediction of hepatitis in Guangxi Province, China by using back propagation neural networks based genetic algorithm (BPNN-GA), generalized regression neural networks (GRNN), and wavelet neural networks (WNN). In order to compare the results of forecasting, the data obtained from 2004 to 2013 and 2014 were used as modeling and forecasting samples, respectively. The results show that when the small data set of hepatitis has seasonal fluctuation, the prediction result by BPNN-GA will be better than the two other methods. The WNN method is suitable for predicting the large data set of hepatitis that has seasonal fluctuation and the same for the GRNN method when the data increases steadily.

Keywords: Evaluation; Forecasting; Hepatitis; Neural networks method.

Grants and funding

This work was supported by the project of basic ability promotion for young teachers of Guangxi education department (KY2016YB093). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.