Generation Of Experimental Design Research Articles

Optimal Design of Steel Columns with Axial Load Using Artificial Neural Networks

This study presented a design of experiences approach to solve this problem, whose steps include: 1 generation of experimental design 2 implementation of experimental design 3 construction of response variable model 4 definition of optimization problem 5 solution of optimization problem. The above step 1 to 3 is to create a model of response variables to be as an alternative for structural analysis software, and because the model is a set of regular and simple functions, it can easily define the optimization problem in step 4, and then the optimization problem can be solved with optimization software in step 5. The reason that neural network is employed instead of the traditional regression analysis in step 3 is in structures the relations between internal forces and displacements and section size of members are often nonlinear. The greatest advantage of neural networks is that it is a nonlinear system; hence, it can very precisely build a nonlinear model. In this paper, the optimization of cross section of compressive steel column is employed as the case studies to assess the feasibility of the approach. The results show that this approach can indeed get a more economical design.