ZA22/Al2O3f复合材料机械性能的神经网络模拟研究

NEURAL NETWORK SIMULATION ON MECHANICAL PROPERTIES OF ZA22/Al2O3f COMPOSITES

  • 摘要: 采用人工神经网络的典型模型即B-P算法对ZA22/Al2O3f复合材料的机械性能进行分析和预测,结果表明:B-P模型不仅适用于单变量输出非线性系统的拟合与预测,同时还适用于多变量输出的非线性系统;B-P模型对研究复合材料ZA22/Al2O3f的机械性能有良好容错性.

     

    Abstract: The typical model of neural network e.g.B-P algorithm was adopted to analyze as well as predict the mechanical properties of ZA22/Al2O3f composites.The results show that B-P model is not only suitable for the regression and prediction for the single variable output non-linear system,but also suitable for the multi-variables output non-linear system.Perfect fault tolerance ability was also found in the B-P model while it was used to analyze the mechanical properties of ZA22/Al2O3f composites.

     

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