The Analysis of Building Subsidence Prediction Based on Grey Model Combined with Radial Basis Neural Network
- Release time:2024-08-09
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Affiliation of Author(s):
理学院
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Journal:
Advanced Materials Research
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Key Words:
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
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Abstract:
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.
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Note:
白燕
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Co-author:
曾凡奎
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First Author:
任庆昌,baiyan
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Indexed by:
Journal paper
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Volume:
卷：368-373
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Issue:
期：
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Page Number:
页：2359-2363
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Translation or Not:
no
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Date of Publication:
2011-11-01
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