Seismic Damages Prediction For Single-Story Reinforced Concrete Industrial Building

Based on thorough analysing the factors which affect the seismic damage of single-story reinforced concrete industrial building,this paper introduces two kinds of methods which are applicable to prediction of seismic damage for single-story reinforced concrete industrial building.One is BP(Back Propagation) neural network method,which is based on the theory of artifical neural network.In this method,LM(Levenberg-Marquardt) optimization algorithm is applied to improve the performance of standard BP algorithm.The other is grey fixed weight cluster method, which is based on the theory of grey system. In this method,the clustering weights of the factors are determined by analytical hieratchy process,it can decrease influence of personal factors and the result of the prediction is more objective.Some examples proved that these two kinds of methods are practicable and efficient in the field of seismic damage prediction of structures,both of them are worthy of making further research and promoting in future.