Abstract

Abstract In this study, to find the global optimum efficiently, holographic neural network is introduced to be an activate function of response surface methodology. Since the accuracy of approximation function near the global optimal design is merely important, techniques to search the region of containing the global optimal design using conditional random seeds, and techniques for finding more, accurate approximation near the global optimal design, using holographic neural network are exploited. In the study, the proposed approach called the most probable optimal design (MPOD) method to pick up one local optimum design which has the biggest probability in the design space. Design example of crash worthiness for the passenger injury with continuous and discrete design variables are shown the validity of the method.

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