基于模糊神经网络和遗传算法的产品造型设计  

Applying Hybrid Approach Based on Fuzzy Neural Network and Genetic Algorithm to Product Form Design

作　　者：刘刚田[1] 曹慧敏[1] 宋晓磊[2] 

机构地区：[1]河南科技大学,河南洛阳471003 [2]机械工业出版社,北京100037

出　　处：《煤矿机械》2009年第11期205-208,共4页Coal Mine Machinery

基　　金：河南省教育厅自然科学基金项目(2006460003);河南科技大学科研基金资助项目(2008ZY056;2006QN039)

摘　　要：提出了基于模糊神经网络和遗传算法完成产品自动搜索和产品形象评价的一种方法,构造基于特征层次的计算机辅助设计(CAD)模型,对相关造型参数进行界定,自动生成新的产品造型。利用模糊神经网络算法建立输入造型参数和系列形容形象词语的关系。在反馈过程中,遗传算法通过训练神经网络满足产品形象合理功能的设计要求来搜索理想的最优化设计。该方法提供了一个使设计人员能迅速获得产品造型及其相应的图像或在短时间的理想造型中寻找到符合形象要求的自动设计系统。Proposes a method which enables an automatic product form search and product image evaluation by means of fuzzy neural network and genetic algorithm. A feature-based hierarchical computer-aided design （CAD） model is constructed, in which the related form parameters are thoroughly defined in applicable domains to facilitate the automatic generation of new product forms. A fuzzy neural network algorithm is applied to establish the relationships between the input form parameters and a series of adjectival image words. In a reverse process, genetic algorithm is employed to search for a near-optimal design which satisfies the designer＇s required product image by using the trained neural network as a fitness function. The proposed method provides an automatic design system, which gives designers the ability to rapidly obtain a product form and the corresponding image, or to search for the ideal form which fits a required image in a shorter lead-time.

关 键 词：计算机辅助设计 模糊神经网络 遗传算法 产品造型设计 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]