中文摘要：

目的 使用R语言分析模型对结核病发病率数据进行演算与分析,探索较佳的分析模型.方法 使用重庆市1993-2007年结核病发病登记数作为建模数据,采用R语言中的神经网络模型和灰色模型分别预测2008年与2009年的发病人数,并与其对应年份的真实发病人数进行比较.结果 采用神经网络模型预测结果误差分别为4.75%、0.83%,灰色模型误差分别为27.08%、49.84%.结论 神经网络模型为较佳分析模型,预测结果对实际工作的量化和资源调配有重要的指导意义.

英文摘要：

Objective To compare two predicting models for tuberculosis （TB） incidence using R language. Methods Recorded numbers of TB patients in Chongqing between 1993 and 2007 were used as modeling data. Neuro - network model and gray model programmed with R language were used to predict the TB incidence in 2008 and 2009, respectively. These pre- dicted TB incidences were compared with the real TB incidences in 2008 and 2009. Results The predicting errors of neuro - net- work model were 4.75% for 2008 and 0. 83% for 2009, while those of gray model were 27.08% for 2008 and 49. 84% for 2009. Conclusion The neuro - network model is more accurate in predicting TB incidence than the gray model.