建立了预测铀钛合金在不同氮气氛和不同相对湿度下贮存后力学性能变化的人工神经网络模型，并用两组已知数据对人工神经网络垢预测效果进行了验证。
An appmach of artificial neural newrk(ANN) was applied to the study of the mechanical properties of U-0.75 %Ti alloy after the alloy stored in nitrcgen amphere with various RH% . Good results were obtained for both of learning and the predicting performance. Using ANN to predict the mechanical properties of U-Ti alloy in nitrcgen amphere after 10 day.
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