Title :
Research on selection of tall building structures based on artificial neural network
Author :
Qin, Li ; Ding, Xiaoying
Author_Institution :
Archit. & Civil Eng., Northeast Dianli Univ., Jilin, China
Abstract :
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 artificial neural network. The qualities of the artificial neural networks (ANN), high-nonlinear, high-permissibility of error and high-robustness, self-adaptability, online work and so on are adequately used in the research. BP neural and RBF neural were used in choice of structural styles respectively. From the research we know that the method based on radial basic function neural network (RBFNN) can solve the problem on choice of structural styles more effectively.
Keywords :
building; radial basis function networks; structural engineering computing; RBF neural networks; artificial neural network; radial basic function neural network; structural design; tall building structures; Artificial neural networks; Buildings; Construction industry; Economics; Electron tubes; Radial basis function networks; Training; BP neural network; RBF neural network; choice of structural Styles; tall building;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5584474