基于 BP 神经网络与 GM（1，1）模型组合算法的桥梁耐久性预测

摘要

Predicting the bridge durability accurately is of great significance for saving maintenance costs and en-suring traffic safty.For this reason,this paper has proposed a combined algorithm based on BP neural network and GM(1,1)model on the basis of the data character of bridge durability.By taking some of the evaluation as a sam-ple,the GM(1,1)model and BP network were used to deal and correct the residual,which aims at improvs the accuracy of the alqorithm and overcome the defect of the single model.Finally,an example shows that the accura-cy of combined algorithm is obviously better than the single GM(1,1)model and also superior to similar method.%针对混凝土桥梁耐久性历史评估数据的特点，提出一种基于 BP 神经网络与 GM（1，1）模型的桥梁耐久性组合预测方法。通过 GM（1，1）模型，以部分数据作为样本进行预测，在此基础之上，引入 BP 神经网络对预测的残差序列进行处理，旨在克服单一预测模型的不足，取得更高的预测精度。算例表明，本文算法精度明显高于传统 GM（1，1）模型，与类似算法相比，精度上也有所提高。