大规模定制设计客户需求处理模型研究

Tao Xi, Lijing Wang, Minghua Shi
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引用次数: 0

摘要

根据大规模定制设计中客户需求信息的实际特点,基于模糊集、粗糙集和支持向量机理论建立了有效的需求信息处理模型。首先,利用模糊集理论对客户需求中的语义属性、模糊信息和连续值进行离散数值处理;然后利用粗糙集理论对大量冗余信息进行属性约简和规则提取;最后,利用支持向量机理论,对产品的特性要求和功能特征进行了约简回归分析。以工程机械设备定制设计为例,说明该模型能有效处理客户需求中基于语义、模糊和需求的冗余信息提取和功能质量映射。
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Research on customer requirements processing model of mass customization design
According to the actual characteristics of the customer requirements information in mass customization design, the requirements information processing model is established based on fuzzy set, rough set and Support vector machine theory of effective. Firstly, the discrete numerical processing of semantic attributes, fuzzy-based information and continuous values in customer demands are carried out with fuzzy set theory. Then the rough set theory is used to reduce attribute and extract rule for a large number of redundant information. Finally, the use of support vector machine theory, reduction properties of the requirements and functional characteristics of products are carried out regression analysis. Acustomization design case of engineering machinery equipment is developed to illustrate that the model can effectively handle the semantic, fuzzy-based and requirements information extraction and function quality mapping of redundancy information in customer requirements.
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