基于ANN及CBR的产品需求映射实现方法

摘要

During the cased-based reasoning procedure of requirement mapping, the randomness and subjectiveness of weight setting always lead to the poor accuracy of results affected by irrelevant noise. A new method of CBR weight setting has been put forward to solve it based on ANN, which defined the relevant weight from the aspects of feature sensitivity, activity, saliency, relevance and the transforming mechanism of features input also been described. Based on it, a new requirement mapping procedure module has been put forward oriented to CBR and verified with the design of the hydraulic workbench, which gives a new method for product requirement mapping.%针对基于实例推理的产品需求映射实现过程中,指标权重设定的随机性及主观性导致无关的噪音特征影响结论的准确性等状况,提出了基于神经网络的CBR权值学习方法(即通过特征灵敏度、活跃度、凸度、相关度进行权值定义),以及输入特征的转换机制,在此基础上给出了基于CBR的产品需求映射过程模型,并将上述模型在移动工作台需求映射实现中进行了应用,系统实现表明了提出方法的有效性,为产品需求映射提供了一种新的有效实现途径.