Comparison of Two Hybrid Models for Forecasting the Incidence of Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China
暂无分享,去创建一个
Wei Wu | Peng Guan | Hiroshi Nishiura | Junqiao Guo | H. Nishiura | Wei Wu | Shu-yi An | P. Guan | Baosen Zhou | Baosen Zhou | Yangwu Ren | Shuyi An | Junqiao Guo | Linzi Xia | Yangwu Ren | Linzi Xia | Junqiao Guo
[1] S. Tong,et al. Seasonal rainfall variability, the incidence of hemorrhagic fever with renal syndrome, and prediction of the disease in low-lying areas of China. , 1998, American journal of epidemiology.
[2] Tao Zhang,et al. Comparative Study of Four Time Series Methods in Forecasting Typhoid Fever Incidence in China , 2013, PloS one.
[3] Ying Wang,et al. A Hybrid Model for Predicting the Prevalence of Schistosomiasis in Humans of Qianjiang City, China , 2014, PloS one.
[4] Wu-Chun Cao,et al. Landscape Elements and Hantaan Virus–related Hemorrhagic Fever with Renal Syndrome, People’s Republic of China , 2007, Emerging infectious diseases.
[5] P. Guan,et al. Forecasting model for the incidence of hepatitis A based on artificial neural network. , 2004, World journal of gastroenterology.
[6] S. Tong,et al. Climatic, reservoir and occupational variables and the transmission of haemorrhagic fever with renal syndrome in China. , 2002, International journal of epidemiology.
[7] Donald F. Specht,et al. A general regression neural network , 1991, IEEE Trans. Neural Networks.
[8] G. Song. Epidemiological progresses of hemorrhagic fever with renal syndrome in China. , 1999, Chinese medical journal.
[9] W. Yang,et al. Prevalence of haemorrhagic fever with renal syndrome in mainland China: analysis of National Surveillance Data, 2004–2009 , 2011, Epidemiology and Infection.
[10] Buse Melis Ozyildirim,et al. Generalized classifier neural network , 2013, Neural Networks.
[11] Å. Lundkvist,et al. Predicting High Risk for Human Hantavirus Infections, Sweden , 2009, Emerging infectious diseases.
[12] J. J. Montaño Moreno,et al. Artificial neural networks applied to forecasting time series. , 2011, Psicothema.
[13] B. Grenfell,et al. Animal Reservoir, Natural and Socioeconomic Variations and the Transmission of Hemorrhagic Fever with Renal Syndrome in Chenzhou, China, 2006–2010 , 2014, PLoS neglected tropical diseases.
[14] Weizhong Yang,et al. Forecasting incidence of hemorrhagic fever with renal syndrome in China using ARIMA model , 2011, BMC infectious diseases.
[15] Weirong Yan,et al. A hybrid model for short-term bacillary dysentery prediction in Yichang City, China. , 2010, Japanese journal of infectious diseases.
[16] Feng Wang,et al. A hybrid seasonal prediction model for tuberculosis incidence in China , 2013, BMC Medical Informatics and Decision Making.
[17] Dragutin Lisjak,et al. Estimation of chemical resistance of dental ceramics by neural network. , 2008, Dental materials : official publication of the Academy of Dental Materials.
[18] Ying Wang,et al. Application of a New Hybrid Model with Seasonal Auto-Regressive Integrated Moving Average (ARIMA) and Nonlinear Auto-Regressive Neural Network (NARNN) in Forecasting Incidence Cases of HFMD in Shenzhen, China , 2014, PloS one.
[19] H. Ren,et al. The development of a combined mathematical model to forecast the incidence of hepatitis E in Shanghai, China , 2013, BMC Infectious Diseases.
[20] Qi Li,et al. Application of an autoregressive integrated moving average model for predicting the incidence of hemorrhagic fever with renal syndrome. , 2012, The American journal of tropical medicine and hygiene.
[21] F. Chen,et al. The Spatial Analysis on Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China Based on Geographic Information System , 2014, PloS one.
[22] Shiwen Wang,et al. Changes in age distribution of hemorrhagic fever with renal syndrome: an implication of China’s expanded program of immunization , 2013, BMC Public Health.
[23] X. Miao,et al. Application of a Hybrid Model for Predicting the Incidence of Tuberculosis in Hubei, China , 2013, PloS one.
[24] L. Fang,et al. [Study on the application of geographic information system in spatial distribution of hemorrhage fever with renal syndrome in China]. , 2003, Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi.
[25] Les E. Atlas,et al. Recurrent neural networks and robust time series prediction , 1994, IEEE Trans. Neural Networks.
[26] John Vontas,et al. A Simple Colorimetric Assay for Specific Detection of Glutathione-S Transferase Activity Associated with DDT Resistance in Mosquitoes , 2010, PLoS neglected tropical diseases.