This paper introduces the basic principle and characteristic of genetic algorithm (called GA), and it points out the shortcoming of ordinary optimum algorithm and the merit of GA. Comparing the optimum results of GA with accurate value by exemplification, and it is good. This paper provides a systematic thought model and a good method for readers.

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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