| 矿渣微晶玻璃材料设计神经网络模型 |
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| 引用本文： | 文岐业,张培新,张怀武.矿渣微晶玻璃材料设计神经网络模型[J].无机材料学报,2003,18(3):561-568. |
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| 作者姓名： | 文岐业 张培新 张怀武 |
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| 作者单位： | 1. 电子科技大学微电子与固体电子学院,成都,610054
2. 深圳大学师范学院化学与生物学系,深圳,518060;广西大学化学化工学院,南宁,530004 |
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| 基金项目： | 广东省自然科学基金(021289),广西科学基金(桂科青0135020) |
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| 摘 要： | 研究了人工神经网络在矿渣微晶玻璃材料设计中的应用．采用基于变尺度法的新学习算法建立了三层前馈型神经网络,发现当网络结构为M-2M-1,取一定范围内的学习误差时,网络具有很好的学习效果．研究证明,建立的人工神经网络模型学习速度快,收敛稳定,强壮性好,能根据较少的实验样本有效抽取矿渣微晶玻璃组成、工艺和性能之间的内在规律,是进行微晶玻璃材料设计的有力工具．
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| 关 键 词： | 人工神经网络 矿渣微晶玻璃 材料设计 |
| 文章编号： | 1000-324X(2003)03-0561-08 |
| 收稿时间： | 2002-3-18 |
| 修稿时间： | 2002年3月18日 |
Applications of Artificial Neural Network in Slag Glass-Ceramic Expert System |
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| WEN Qi-Ye,ZHANG Pei-Xin,ZHANG Huai-Wu.Applications of Artificial Neural Network in Slag Glass-Ceramic Expert System[J].Journal of Inorganic Materials,2003,18(3):561-568. |
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| Authors: | WEN Qi-Ye ZHANG Pei-Xin ZHANG Huai-Wu |
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| Affiliation: | 1.CollegeofMicro-ElectronicandSolid-Electronic;UniversityofElectronicScienceandTechnologyofChina;Chengdu610054;China;2.NormalCollege;ShenzhenUniversity;Shenzhen518060,Chiina;3.CollegeofChemistryandChemicalEngineering;GuangxiUniversity;Nanning530004;China |
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| Abstract: | Artificial neural network was introduced into slag glass-ceramic material designing. A 3 layers feedforward network was built with a new robust learning algorithm, based on a concept of " entire error modifying ". The network has a excellent learning ability when its topology is M-2M-1 and an appropriate study error chosen. The research results show that this slag glass-ceramic neural network is robust, quick and stable in training and data predicting, which can disclose the relationship of elemental compositions, structure and material properties of slag glass-ceramic effectively, even if some parameters are absent in samples. |
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| Keywords: | artificial neural network slag glass-ceramic material designing |
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