基于对变形镍基高温合金在不同温度和时间条件下合金成分及其持久强度数据归一化处理后的反向传播神经网络模拟,得到了可以比较准确表达持久强度与合金成分、温度和时间之间复杂非线性关系的权值矩阵,由此可以对镍基合金在不同温度和时间条件下的持久强度进行预测.结果表明,用神经网络预测的持久强度与实验结果吻合良好,从而证实了该网络模型的准确性和适用性.
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