An integration method of artificial neural network and genetic algorithm for structure design of a scooter

Abstract

In this paper, an integration method of the artificial neural network (ANN) system and the genetic algorithms (GA) was proposed. Computer aided engineering (CAE) simulations and experiments were carried out to analyze the deformation of a four-wheel scooter under different loading conditions. A prototype of scooter structure was built to verify the simulation and design results. The simulation results of stress, strain and displacement data were adopted for the training and testing of the developed ANN system. The trained ANN system was integrated with the optimization system based on the genetic algorithm to determine the most suitable combination of the structure design. The material types, topological configurations and section geometries of structural beams were taken into consideration of design. The predicted deformation results of the ANN system were in good agreement with the CAE and experiment data. © Springer-Verlag Berlin Heidelberg 2006.