一种面向领域的组件质量度量算法

    A Component Quality Metrics Algorithm Facing to Field

    • 摘要: 为了满足特定领域对组件特性的特殊要求,提出了一种基于神经网络的组件质量度量算法.该算法采用了定量度量的方法,为不同特性赋予不同权重,取代了传统度量过程中对组件特性的定性评价方法,增强了组件度量的准确性.该算法通过机器学习的方法增强了自己的度量能力.

       

      Abstract: In order to satisfy the certain field's special request for component's specialities, the authors described an algorithm based on Neural Networks by giving each speciality a metrics weight. Instead of inden-tification metrics in the traditional process, this algorithms is based on quantitative metrics. So the precision of component metrics is improved. The algorithms can update itself by machine learning.

       

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