“…Some of the methods have been used in engineering or architectural designs, including poly-nominal regression and response surface method (RSM) [16,[27][28][29], multi-layer perceptron neural network (MLPNN) [15,29] [30,31], random forest (RF) [15,32,33], radial basis function network (RBFN) [14,15], kriging [15,34,35]. In [15], these methods are used to support surrogate models for a long-span building design focusing on structural self-weight and energy. The results in [15] indicated that the MLPNN has the fastest speed and smallest errors in the data approximation of structural weight and energy consumption for the design example.…”