The model is good by predicting protein concentration of wheat flour with different unknown sample groups. Its error is less than 1 0.
对不同未知样本进行了预测，结果表明，所建模型具有一定的稳定性，对未知样品蛋白质浓度的测量偏差较小，其最大偏差不超过1 .0。
The results show that BP artificial neural network can be used in predicting mechanical properties and grain size of materials after superplastic forming and its predicting error is less than 7%.
结果表明，BP神经网络用于材料超塑性变形后的力学性能及晶粒尺寸预测是可行的，其预测误差小于7%。
The results show that BP artificial neural network can be used in predicting mechanical properties and grain size of materials after superplastic forming and its predicting error is less than 7%.
结果表明，BP神经网络用于材料超塑性变形后的力学性能及晶粒尺寸预测是可行的，其预测误差小于7%。
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