摘要
文对贝叶斯模型进行改进,构建实时数据融合模型,改进后的贝叶斯模型在多源异构实时数据融合中的表现显著优于其他模型。从均方误差和平均绝对误差两个关键指标来看,改进后的贝叶斯模型的MSE为469.52,MAE为109.27,均为所有模型中最低。
This article improves the Bayesian model and constructs a real-time data fusion model.The improved Bayesian model performs significantly better than other models in multi-source heterogeneous real-time data fusion.From the two key indicators of mean square error and mean absolute error,the MSE of the improved Bayesian model is 469.52,and the MAE is 109.27,both of which are the lowest among all models.
出处
《现代传输》
2025年第1期33-36,共4页
Modern Transmission
