摘要
在传统的客户需求映射方法中,客户需求的权重通常是通过专家评分法确定的,很难反映客户对产品的真实需求。综合运用模糊理论和神经网络方法,建立了模糊客户需求映射模型,对客户需求矢量进行了仿真实验,预测出客户需求的实际权重,建立了反映真实需求的模糊度量质量屋。最后,通过实例验证了该方法的有效性。
The weights of customer requirements are confirmed generally by expert evaluation method in traditional mapping method of customer requirements, which reflects hardly true customer requirements. Eestablished the model of fuzzy customer requirements mapping, simulated the vectors of customer requirements in Matlab 7.0, forecasted the real weights of customer requirements by using the theory of fuzzy set and the method of neural networks, and built a actual fuzzy measurable house of quality. Finally, we validate the efficiency of the method.
出处
《机械设计与制造》
北大核心
2007年第1期42-44,共3页
Machinery Design & Manufacture
基金
国家973计划项目(2004CB719405)
关键词
客户需求
模糊
神经网络
Customer requirements
Fuzzy
Neural networks