In this study, we carried out nonlinear finite element simulations to predict the performance of a column-tree moment connection (CTMC) under fire and static loads. We also conducted a detailed parameter study based on five input variables, including the applied temperature, number of flange bolts, number of web bolts, length of the beam, and applied static loads. The first variable is changed among seven levels, whereas the other variables are changed among three levels. Employing the Taguchi method for variables 2–5 and their levels, 9 samples were designed for the parameter study, where each sample was exposed to 7 different temperatures yielding 63 outputs. The related variables for each output are imported for the training and testing of different surrogate models. These surrogate models include a multiple linear regression (MLR), multiple Ln equation regression (MLnER), an adaptive network-based fuzzy inference system (ANFIS), and gene expression programming (GEP). 44 samples were used for training randomly while the remaining samples were employed for testing. We show that GEP outperforms MLR, MLnER, and ANFIS. The results indicate that the rotation and deflection of the CTMC depend on the temperature. In addition, the fire resistance increases with a decrease in the beam length; thus, a shorter beam can increase the fire resistance of the building. The numbers of flanges and web bolts slightly affect the rotation and displacement of the CTMCs at temperatures of above 400°C.

在这项研究中，我们进行了非线性有限元模拟，以预测在火荷载和静荷载下的柱-树弯矩连接（CTMC）的性能。我们还基于五个输入变量进行了详细的参数研究，包括所施加的温度，法兰螺栓的数量，腹板螺栓的数量，梁的长度以及所施加的静载荷。第一个变量在七个级别之间更改，而其他变量在三个级别之间更改。使用Taguchi方法对变量2–5及其水平进行设计，设计了9个样本用于参数研究，其中每个样本都暴露于7种不同的温度下，可产生63个输出。导入每个输出的相关变量，以训练和测试不同的代理模型。这些替代模型包括多元线性回归（MLR），多Ln方程回归（MLnER），基于自适应网络的模糊推理系统（ANFIS）和基因表达编程（GEP）。44个样本用于随机训练，其余样本用于测试。我们表明，GEP的表现优于MLR，MLnER和ANFIS。结果表明，CTMC的旋转和偏转取决于温度。另外，耐火性随着光束长度的减小而增加。因此，较短的光束可以提高建筑物的耐火性。在高于400°C的温度下，法兰和腹板螺栓的数量会稍微影响CTMC的旋转和位移。44个样本用于随机训练，其余样本用于测试。我们表明，GEP的表现优于MLR，MLnER和ANFIS。结果表明，CTMC的旋转和偏转取决于温度。另外，耐火性随着光束长度的减小而增加。因此，较短的光束可以提高建筑物的耐火性。在高于400°C的温度下，法兰和腹板螺栓的数量会稍微影响CTMC的旋转和位移。44个样本用于随机训练，其余样本用于测试。我们表明，GEP的表现优于MLR，MLnER和ANFIS。结果表明，CTMC的旋转和偏转取决于温度。另外，耐火性随着光束长度的减小而增加。因此，较短的光束可以提高建筑物的耐火性。在高于400°C的温度下，法兰和腹板螺栓的数量会稍微影响CTMC的旋转和位移。