Structural form selection of the high-rise building with the improved BP neural network

• Published in: 高技术通讯（英文版） Vol. 26; no. 1; pp. 92 - 97
• Main Authors: 赵光哲, Yang Hanting, Tu Bing, Zhou Meiling, Zhou Chengle
• Format: Journal Article
• Language: Chinese
• Published: School of Electrical and Information Engineering, Beijing University of Civil Engineeringand Architecture, Beijing 100044, P. R. China%College of Information and Communication Engineering, Hunan Institute of Science and Technology, Yueyang 414000, P. R. China 2020
• Subjects: Levenberg-Marquardt ( L-M) algorithm; high-rise building; back propagation ( BP) neural network; structural form selec-tion
• ISSN: 1006-6748
• DOI: 10.3772/j.issn.1006-6748.2020.01.012

As civil engineering technology development, the structural form selection is more and more critical in design of high-rise buildings. However, structural form selection involves expertise knowl-edge and changes with the environment which makes the task arduous. An approach utilizing im-proved back propagation ( BP) neural network optimized by the Levenberg-Marquardt ( L-M) algo-rithm is proposed to extract the main controlling factors of structural form selection. Then, an intelli-gent expert system with artificial neural network is constructed to design high-rise buildings structure effectively. The experiment tests the model in 15 well-known architecture samples and get the predic-tion accuracy of 93 . 33％. The results show that the method is feasible and can help designers select the appropriate structural form.