| 人工神经网络在玻璃纤维弹性模量预测中的应用 |
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| 引用本文： | 刘晓勇,孟庆红,谢春来,孙泽波.人工神经网络在玻璃纤维弹性模量预测中的应用[J].硅酸盐通报,2009,28(4):824-828. |
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| 作者姓名： | 刘晓勇 孟庆红 谢春来 孙泽波 |
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| 作者单位： | 河北建材职业技术学院,秦皇岛,066004;秦皇岛北方玻璃集团有限公司,秦皇岛,066004;秦皇岛玻璃工业研究设计院,秦皇岛,066000 |
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| 摘 要： | 传统玻璃成分设计方法不仅计算繁琐、工作量大,效率低,而且精度较低,生产者迫切希望能改进玻璃成分设计方法.计算机辅助建模大大缩短了新材料、新工艺和新设计从实验室转移到生产现场所需的时间,为玻璃成分设计提供了强有力的技术支持.人工神经网络是用工程技术手段模拟生物神经网络结构特征的一类人工系统.它具有很强的自学习能力,能够从已有的实验数据中获取有关材料的组分、工艺和性能之间的规律,并达到预测的目的.本文主要研究了人工神经网络在玻璃成分设计中,尤其是在预测玻璃性能方面的应用.
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| 关 键 词： | 人工神经网络 玻璃纤维弹性模量 性能预测 |
Application of Artificial Neural Networks in the Modulus of Elasticity Forecast of Fiberglass |
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| LIU Xiao-yong,MENG Qing-hong,XIE Chun-lai,SUN Ze-bo.Application of Artificial Neural Networks in the Modulus of Elasticity Forecast of Fiberglass[J].Bulletin of the Chinese Ceramic Society,2009,28(4):824-828. |
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| Authors: | LIU Xiao-yong MENG Qing-hong XIE Chun-lai SUN Ze-bo |
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| Affiliation: | LIU Xiao-yong1,MENG Qing-hong1,XIE Chun-lai2,SUN Ze-bo3(1.Hebei Building Material Vocational and Technical College,Qinhuangdao 066004,China,2.Qinghuangdao Beifang Class Group Co.,Ltd,3.Qinhuangdao Glass Industry Research and Design Institute,Qinhuangdao 066000,China) |
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| Abstract: | The traditional design method of glass composition not only is with multifarious calculation,heavy workload and low efficiency but also precision is low.So a new approach to improve design method is expected thirstily for producers.Computer aided modeling will shorten the conversion time from experimentation to produce of new materials,techniques and design.It offer the effectively technique support for designing glass composition.Artificial neural networks is an artificial system which simulate biological ... |
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| Keywords: | artificial neural networks modulus of elasticity forecast of fiberglass performance forecast |
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