基于RBF神经网络的肠道细菌宿主年龄预测研究

Research on the age prediction of intestinal bacterial hosts based on RBF neural network

径向基函数(RBF)神经网络,具有收敛速度快、局部逼近精度高和一定的鲁棒性等优点,广泛运用于非线性函数逼近、数据预测和数据分类等问题。基于RBF神经网络的特点,以肠道细菌宿主的16个指标作为自变量,对宿主个体的年龄进行预测以及误差值分析。结果表明:RBF神经网络下宿主个体的年龄预测在训练集和测试集上均表现出较好的均方误差MSE、均方根误差RMSE、平均绝对百分比误差MAPE以及相关系数R^(2)四个评价指标。测试集年龄的预测值非常接近实际值,两者间的误差值较小,预测精度较高,具有很好的预测能力。这为研究肠道细菌宿主的身体健康提供咨询指导,具有一定的理论研究意义与应用价值。

Radial basis function(RBF)neural network,which has the advantages of fast convergence speed,high local approximation accuracy and certain robustness,is widely used in nonlinear function approximation,data prediction and data classification.Based on the characteristics of RBF neural network,16 indicators of intestinal bacterial hosts are used as independent variables to predict the age of individual hosts and analyze the error values.The result shows that:The age prediction of host individuals under RBF neural network shows good mean square error MSE,root mean square error RMSE,mean absolute percentage error MAPE and correlation coefficient R^(2) in both the training set and the test set.The predicted age values in the testing set are very close to the actual values,and the error between the two is small and the prediction accuracy is high,so it has good predictive ability.This experiment provides consultation and guidance for the study of the physical health of intestinal bacterial hosts,and has certain theoretical research significance and application value.