基于GA-BP神经网络的布鲁氏菌病的预测研究
Study on the Prediction of Brucellosis Based on GA-BP Neural Network

布鲁氏菌病在我国是一种法定乙类传染病，近年来布鲁氏菌病患病人数增多，对布鲁氏菌病建立预测模型，对该病的预防和控制有着重要的意义。本文基于2004年~2020年布鲁氏菌病的月发病率数据，建立BP神经网络、遗传算法优化的BP神经网络模型，对我国的布鲁氏菌病进行预测，用MAE、MAPE、MSE、RMSE四个指标比较模型的预测精度。研究结果表明，遗传算法优化的BP神经网络模型的预测精度优于BP神经网络，所以遗传算法优化的BP神经网络模型对布鲁氏菌病的预测效果更好。
Brucellosis in China is a legal group B infectious disease, in recent years, the number of patients with brucellosis has increased, and the establishment of a prediction model for brucellosis has important significance for the prevention and control of the disease. In this paper, based on the monthly incidence data of brucellosis from 2004 to 2020, a model of BP neural network and BP neural network optimized by genetic algorithm was established to predict brucellosis in China. MAE, MAPE, MSE and RMSE were used to compare the prediction accuracy of the model. The results show that the prediction accuracy of BP neural network model optimized by genetic algorithm is better than that of BP neural network, so the BP neural network model optimized by genetic algorithm has better prediction effect on brucellosis.