ZA22/Al<sub>2</sub>O<sub>3f</sub>复合材料机械性能的神经网络模拟研究

ZA22/Al₂O_3f复合材料机械性能的神经网络模拟研究

基金项目: 国家自然科学基金

详细信息

1.
Department of Chemical Engineering, Zhejiang University, Hangzhou 310027;
2.
Department of Metallic Material Engineering, Jilin University of Technology, Changchun 130025

摘要

摘要: 采用人工神经网络的典型模型即B-P算法对ZA22/Al₂O_3f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/Al₂O_3f的机械性能有良好容错性.
- 锌铝合金 /
- 复合材料 /
- 机械性能 /
- 神经网络
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/Al₂O_3f 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/Al₂O_3f composites.
- ZA22alloy /
- composite /
- mechanical property /
- neural network