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Weighted Markov chains for forecasting and analysis in Incidence of infectious diseases in jiangsu Province,China 被引量:10
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作者 Zhihang Peng Changjun Bao +5 位作者 Yang Zhao Honggang Yi Letian Xia Hao Yu Hongbing Shen Feng Chen 《The Journal of Biomedical Research》 CAS 2010年第3期207-214,共8页
This paper first applies the sequential cluster method to set up the classification standard of infectious disease incidence state based on the fact that there are many uncertainty characteristics in the incidence cou... This paper first applies the sequential cluster method to set up the classification standard of infectious disease incidence state based on the fact that there are many uncertainty characteristics in the incidence course.Then the paper presents a weighted Markov chain,a method which is used to predict the future incidence state.This method assumes the standardized self-coefficients as weights based on the special characteristics of infectious disease incidence being a dependent stochastic variable.It also analyzes the characteristics of infectious diseases incidence via the Markov chain Monte Carlo method to make the long-term benefit of decision optimal.Our method is successfully validated using existing incidents data of infectious diseases in Jiangsu Province.In summation,this paper proposes ways to improve the accuracy of the weighted Markov chain,specifically in the field of infection epidemiology. 展开更多
关键词 weighted.Markov chains sequential cluster infectious diseases forecasting and analysis Markov chain Monte Carlo
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