Title :
Application of BP Neural Networks to Choosing style of Transfer Story in Complicated Tall Buildings
Author :
Lin, Huang-Bin ; Wang, Quan-Feng ; Zhang, Yun-Bo ; Zeng, Qi-Fang ; Chu, Shao-feng
Author_Institution :
Huaqiao Univ., Quanzhou
Abstract :
In this paper, 62 cases of tall buildings with transfer story are collected, a unified expression mode of case information in the building is set up for structure scheme design. In choosing structural style for a tall building with transfer story, main control factors arc drawn, with which a mathematical model is formed on the basis of BP (back-propagation) neural networks. Traditional BP algorithm and levernberg-Marquert (L-iYI) algorithm are adopted to research the style-selection of transfer story in tall buildings, respectively. Indicated by the research results, L-M algorithm solves the style-selection preferably for the complicated tall building structures with transfer story. This paper also paves the way for further development of the integrated, intelligent, scientific style-selection of complicated tall buildings with transfer story.
Keywords :
backpropagation; neural nets; structural engineering computing; Levernberg-Marquert algorithm; backpropagation neural networks; complicated tall buildings; structure scheme design; Architecture; Artificial neural networks; Buildings; Civil engineering; Decision making; Design optimization; Intelligent structures; Mathematical model; Neural networks; Uncertainty; Back-Propagation Neural Net; levernberg-Marquert algorithm; structural style-selection; tall building; transfer story;
Conference_Titel :
Integration Technology, 2007. ICIT '07. IEEE International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
1-4244-1092-4
Electronic_ISBN :
1-4244-1092-4
DOI :
10.1109/ICITECHNOLOGY.2007.4290501