| 用人工神经网络预测混杂复合材料混杂效应 |
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| 引用本文： | 曾金芳,乔生儒,李瑞珍,丘哲明,郝志彪.用人工神经网络预测混杂复合材料混杂效应[J].玻璃钢/复合材料,2003(5):7-9. |
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| 作者姓名： | 曾金芳 乔生儒 李瑞珍 丘哲明 郝志彪 |
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| 作者单位： | 1. 西北工业大学,西安,710072
2. 陕西非金属材料工艺研究所 |
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| 摘 要： | 本研究建立一个二输入单输出的BP人工神经网络模型，并用QBASIC语言编制了相应的软件。利用该神经网络模型对混杂效应与混杂比及分散度系数间关系进行了预测。研究结果表明，网络经过61223次的迭代，预潮值误差为0．12％，具有很高的预测精度，可用于混杂复合材料混杂效应的预测。
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| 关 键 词： | 人工神经网络 预测 混杂复合材料 混杂效应 |
| 修稿时间： | 2003年4月9日 |
PREDICTION OF HYBRID EFFECT OF HYBRID COMPOSITES BY ARTIFICIAL NEURAL NETWORKS |
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| Zeng Jinfang,Qiao Shengru,Li Ruizhen.PREDICTION OF HYBRID EFFECT OF HYBRID COMPOSITES BY ARTIFICIAL NEURAL NETWORKS[J].Fiber Reinforced Plastics/Composites,2003(5):7-9. |
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| Authors: | Zeng Jinfang Qiao Shengru Li Ruizhen |
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| Affiliation: | Northwest Polytechnical University |
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| Abstract: | A model of BP artificial neural networks(ANN) with two inputs and single output was established, and relevant software was produced with Qbasic language in the investigation. The relations between hybrid effect coefficient with hybrid ratio and disperse coefficient were predicted. The results showed that, after 61233 times iteration, the error of the predicted value was 0.12% and had very high predicted accuracy. ANN could be used to hybrid effect coefficient prediction of hybrid composites. |
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| Keywords: | hybrid composite hybrid effect artificial neural networks(ANN) |
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