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针对产品质量特性(Quality Characteristics,QCs)重要度人工识别困难的情况,提出了基于人工神经网络(ANNs)技术的产品寿命周期QCs重要度识别模型。首先提取QCs特征参数并对其归一化,建立QCs特征参数向量,其次利用ANNs技术确定QCs特征参数重要度,建立QCs特征参数重要度向量,然后再次利用ANNs并以QCs特征参数重要度向量为模型的输入,建立QCs重要度识别模型,最后给出产品寿命周期QCs重要度识别框图,指导产品寿命周期QCs重要度的识别。仿真实例验证了所提理论与方法的正确性和有效性。
Aiming at the difficulty of manual identification of the importance of Quality Characteristics (QCs), a model of QCs importance identification based on Artificial Neural Network (ANNs) technology is proposed. Firstly, the characteristic parameters of QCs were extracted and normalized, and the QCs characteristic parameters were established. Secondly, the importance of QCs characteristic parameters was determined by using ANNs technique, and the importance vectors of QCs were established. Then, the ANNs were used again and the importance vectors of QCs were Model, the establishment of QCs importance identification model, and finally gives the product life cycle QCs importance identification block diagram, guide the life cycle of products to identify the importance of QCs. The simulation example verifies the validity and validity of the proposed theory and method.