[1]邱秀亮,肖世校,张保灿.基于小波神经网络的手足口病发病率预测研究[J].集美大学学报(自然版),2017,22(3):69-73.
 QIU Xiuliang,XIAO Shixiao,ZHANG Baocan.Predicting the Incidence of Hand-foot-mouth Disease Based on Wavelet Neural Network[J].Journal of Jimei University,2017,22(3):69-73.
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基于小波神经网络的手足口病发病率预测研究()
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《集美大学学报(自然版)》[ISSN:1007-7405/CN:35-1186/N]

卷:
第22卷
期数:
2017年第3期
页码:
69-73
栏目:
数理科学与信息工程
出版日期:
2017-05-28

文章信息/Info

Title:
Predicting the Incidence of Hand-foot-mouth Disease Based on Wavelet Neural Network
作者:
邱秀亮肖世校张保灿
(集美大学诚毅学院,福建 厦门 361021)
Author(s):
QIU XiuliangXIAO ShixiaoZHANG Baocan
(Chengyi University College,Jimei University,Xiamen 361021,China)
关键词:
手足口病气象因素小波变换小波神经网络
Keywords:
HFMDmeteorological factorswavelet transformwavelet neural network
文献标志码:
A
摘要:
结合气象因素,提出了基于小波神经网络的手足口病(hand-foot-mouth disease,HFMD)发病率预测模型。为验证模型有效性,进行了对比测试,测试结果如下:2014年7月至12月,厦门市手足口病实际月发病率为(7.4,4.7,24.3,21.1,8.2,2.8)×10-5,小波神经网络模型预测值为(4.3,21.3,15.9,3.5,5.1,27.2)×10-5,BP神经网络模型预测值为(20.1,14.3,1.7,10.6,68.2,0.4)×10-5,灰色预测模型预测值为(49.7,66.7,89.6,120.4,161.6,217.0)×10-5。通过实例分析表明,相比其他的传统的手足口病预测模型,小波神经网络模型具有收敛速度快、预测精度高、误差小的特点。
Abstract:
According to the research on the meteorological factors,a prediction model of incidence of HFMD was proposed based on wavelet neural network.In order to verify the validity of the model,a comparative test was carried out.The results were as follows:the actual monthly incidence of HFMD in Xiamen from July to December 2014 was (7.4,4.7,24.3,21.1,8.2,2.8)×10-5,and the predicted value of wavelet neural network was (4.3,21.3,15.9,3.5,5.1,27.2)×10-5,the predicted value of BP neural network was (20.1,14.3,1.7,10.6,68.2,0.4)×10-5,the predicted value of Grry predicition model was(49.7,66.7,89.6,120.4,161.6,217.0)×10-5.The results obtained from the simulator showed that the forecasting model of the wavelet neural network could evidently decrease prediction error and improve forecasting veracity compared with other models.
更新日期/Last Update: 2017-09-10