The current state of bronchial pneumonia and the incidence of neural network prediction small selection of BP network model to study the incidence of bronchopneumonia relevant circumstances, can be done to prevent a timely manner. Meteorological factors to the monthly average air temperature, air pressure, on average, the monthly mean relative humidity, wind speed, on average, the monthly average precipitation BP neural network model as input, select Zhangjiachuan region in September 2001 to July 2006 on meteorological data and the incidence the number of data, the use of MATLAB neural network toolbox for model training and prediction. Test data show that this model can more accurately the areas of bronchopneumonia Zhangjiachuan incidence on the forecast made.%目前国家有关支气管肺炎发病情况的神经网络预测研究较少,选用BP网络为模型,研究支气管肺炎发病的相关情况,可以做到及时预防.将气象因子月平均气温,月平均气压,月平均相对湿度,月平均风速,月平均降水量作为BP神经网络模型的输入,选取张家川地区2001年9月到2006年7月气象资料和月发病人数资料,采用MATLAB神经网络工具箱进行模型训练与预测.测试数据表明此模型能够较准确的对张家川地区支气管肺炎月发病率做出预测.
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