基于BP神经网络的疾病症状预测模型

The Prediction Model of Disease Symptoms Based on BP Neural Network

疾病症状上报数量反映了当地居民健康状况,准确预测疾病上报的总条数对于预防传染病的发生至关重要。目前,疾病症状的上报、误报、重报问题突出,为了得到准确的患病人数,通过对某地区疾病症状上报数据的训练与预测,建立疾病症状上报总数的BP网络预测模型。研究结果表明,基于BP神经网络的疾病症状上报预测模型具有较高的精度和实用性。

Disease symptoms reported Numbers reflect the health of local residents,accurately predict the numbers is very important to prevent the happening of the infectious diseases.However,the real number of cases is not accurate for the extensive error reporting and re-reporting phenomenon.To get the exact number of cases,in this paper,the BP network prediction model of disease symptom reporting was established by the training and prediction of disease reporting data in one area.Finally,theory analyses and simulation results illustrate that the prediction model of disease symptoms based on BP neural network has higher precision and practicability.