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An Integration Method of Artificial Neural Network and Genetic Algorithm for Structure Design of a Scooter

机译:踏板车结构设计的人工神经网络和遗传算法集成方法

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摘要

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.
机译:本文提出了一种人工神经网络(ANN)系统与遗传算法(GA)的集成方法。进行了计算机辅助工程(CAE)仿真和实验,以分析四轮踏板车在不同载荷条件下的变形。建立了踏板车结构的原型以验证仿真和设计结果。应力,应变和位移数据的仿真结果被用于开发的ANN系统的训练和测试。将训练有素的人工神经网络系统与基于遗传算法的优化系统集成在一起,以确定最合适的结构设计组合。结构梁的材料类型,拓扑结构和截面几何形状均已考虑到设计。 ANN系统的预测变形结果与CAE和实验数据吻合良好。

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