Optimum connection of LSF system braces using the seismic-ANN approach

Hossein Mirzaaghabeik , Hamid Reza Vosoughifar
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引用次数: 1

Abstract

Lightweight steel framing (LSF) has been proposed as an economic and earthquake-resistant system. The tendency of mass constructors to use this system is due to it being a full industrial process. One of the systems that resist lateral load in cold-formed steel structures is the application of braces. Optimization and improvement of connections for these braces have been considered by experts in this field of research. In this paper, experimental studies and normalization and simulation by artificial neural network (ANN) were used. The results of the research have been applied to create a nonlinear relationship. All input and target data must be normalized and then simulation and training by a neural network can be performed. In this research, two layers have been used. One of these is a sigmoid layer. The results show that optimal connections in light weight steel framing systems have suitable plasticity, load capacity and nonlinear relations. Statistical analysis with SPSS software shows that there is no significant difference between the neural network and experimental results (P-Value > 0.05).

用地震神经网络方法优化LSF系统支架的连接
轻钢框架是一种经济、抗震的结构体系。大量建筑商使用该系统的趋势是由于它是一个完整的工业过程。在冷弯型钢结构中,支撑的应用是抵抗横向荷载的系统之一。这些牙套连接的优化和改进已被该研究领域的专家所考虑。本文采用实验研究和人工神经网络(ANN)归一化仿真方法。研究结果已被应用于建立一个非线性关系。所有的输入和目标数据必须经过归一化处理,然后用神经网络进行模拟和训练。在本研究中,使用了两层。其中一个是s形层。结果表明,轻钢框架结构的最优连接具有合适的塑性、承载能力和非线性关系。用SPSS软件进行统计分析表明,神经网络与实验结果无显著差异(p值>0.05)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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