چکیده مقاله
In recent , neural network are considered as robust tools for fast approximation with arbitrary accuracy in time consuming problems Dynamic analysis of structures against the earthquake has the time consuming process, in this study we employ Radial Basis Function RBF , Generalized Regression GR , Back propagation BP and Wavenet Back Propagation WBP neural network , for approximating dynamics time history responses of frame structures RBF , GR and BP are traditional network while WBP is a wavelet neural network as sigmoid activation function of hidden layer neurons are substiluted with wavelets To train WBP the optimum weights are determined using Scaled Conjugate Gradient algorithm SCG Comparison of WBP results with the other network indicates that generality of the properly trained WBP is excellent and all of them can be efficiently used for approximating dynamic analysis of the frame structures
کلیدواژهها
نویسندگان
E.Salajegheh
S.Gholizadeh ph.D. student
S.Gholizadeh
ph D student
شیوه ارجاع
E.Salajegheh, and S.Gholizadeh, ,1385,Comparison of RBF,GR and BP with Wavenet Bach Propagation Neural Networks in Approximation Dynamic Analysis of Structure,7th International Congress on Civil Engineering,Tehran
ارائهشده در
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