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《Sichuan Building Science》 2010-05
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Choice of structural styles for tall building based on radial basis function neural network

WANG Quanfeng,ZHENG Hao ( College of Civil Engineering,Huaqiao University,Quanzhou 362021,China)  
In the early stage of the design process,the design of tall building is a complex work. It needs various knowledge and professional experience for the structural design. A way concerned about the choice of structural styles is put forward based on radial basis function neural network ( RBFNN) in this paper. The qualities of the RBFNN,high-nonlinear,high-permissibility of error and high-robustness,self-adaptability,online work,and so on,are adequately used in the research. And,it is concluded that RBFNN runningspeed is 103~ 104 times faster than traditional BP neural network's algorithm. From the research,the method based on RBFNN can solve the problem on choice of structural styles effectively and quickly.
【CateGory Index】: TU973;TP183
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【Citations】
Chinese Journal Full-text Database 1 Hits
1 WANG Guang-yuan, LU Da-gang, ZHANG Shi-hai (School of Civil Engineering &Architecture, Harbin University of Civil Engineering &Architecture, Harbin 150090, China);On some key problems for choice of structural styles[J];JOURNAL OF HARBIN UNIVERSITY OF CIVIL ENGINEERING AND ARCHITECTURE;2000-01
【Secondary Citations】
Chinese Journal Full-text Database 1 Hits
1 Ou Jinping. Zhang Shihai Liu Xiaoyan. Dong Zhiren.. (Harbin University of Architecture and Engineering) (Nanyang lnstitute of Technology);FUZZY EXPERT SYSTEM FOR DEITERMINATION OF LATERAL LOAD RESISTING SYSTEMS OF R.C. TALL BUILDINGS IN SEISMIC REGION[J];EARTHQUAKE ENGINEERING AND ENGINEERING VIBRATION;1997-02
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