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针对产品配置设计的效率以及配置过程的智能性等问题,以汽车板簧为对象,提出一种基于神经网络(NN)的产品自组织配置设计方法。在规划从客户需求到设计结果的自组织配置设计过程的基础上,结合汽车板簧自组织配置设计的过程和特点,分别采用BP和RBF网络构建汽车板簧结构特征与参数配置的神经网络模型;并运用一定数量的实例样本在Matlab7.1中对所建立的结构和参数配置模型进行了训练与仿真,以验证所提出方法的有效性。
In view of the efficiency of the product configuration design and the intelligence of the configuration process, a self-organizing configuration design method based on the neural network (NN) is proposed. Based on the process of self-organizing configuration design from the customer’s demand to the design result and the process and characteristics of self-organizing configuration design of automotive leaf springs, the neural network models of structural characteristics and parameter configuration of automotive leaf springs are respectively constructed using BP and RBF networks ; And a certain number of example samples are used to train and simulate the established structure and parameter configuration model in Matlab7.1 to verify the effectiveness of the proposed method.