An evaluation of back-propagation neural networks for the optimal design of structural systems: Part Ⅱ. Numerical evaluation

摘要

In the companion paper the neural network training procedures used in the present evaluation were described in detail. Also, in the companion paper, two new training methods that used the derivative information to build global approximations, an a mixed local-global approximation scheme were proposed in addition to the common function- based training method. In this paper, we carry out an exhaustive numerical evaluation of the proposed and existing methods using five test problems with varying complexity. Approximately 1100 test cases were run as part of the numerical evaluations.