所属单位：

理学院

发表刊物：

Advanced Materials Research

关键字：

中文关键字：预测模型;沉降预测;神经网络;灰色模型，英文关键字：Prediction Model;Subsidence Predicting;Neural Netw

摘要：

In this paper, a new prediction model named RBNN-GM(1,1) (Radial Basis Neural Network-Grey Model) model was constructed and used for the analysis of building subsidence prediction for the Palms Together Dagoba in Famen Temple in Shaanxi Province in China. The constructed model can make full use of the advantages of few samples and little information predicting in Grey Theory and swift and self-learning in RBNN. The prediction results show that the combined model is more effective than the common grey model. The proposed combined model for building subsidence prediction may offer scientific rationale for estimating whether the building transmutation exceeds the criterion and provide reference for taking the corresponding safety measures.

备注：

白燕

合写作者：

曾凡奎

第一作者：

任庆昌,白燕

论文类型：

期刊论文

卷号：

卷：368-373

期号：

期：

页面范围：

页：2359-2363

是否译文：

否

发表时间：

2011-11-01