| 基于支持向量机的灰铸铁强度预测模型 |
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| 引用本文： | 龚艳冰,陈森发.基于支持向量机的灰铸铁强度预测模型[J].铸造,2006,55(7):711-714. |
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| 作者姓名： | 龚艳冰 陈森发 |
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| 作者单位： | 东南大学系统工程研究所,江苏,南京,210096 |
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| 摘 要： | 利用高碳当量灰铸铁组织强度试验数据,提出了一种基于支持向量机理论的灰铸铁强度预测模型。与多元线性回归、模糊回归和自适应模糊神经网络相比,该模型学习精度高且具有较好的泛化能力,能取得较好的预测效果。
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| 关 键 词： | 灰铸铁 支持向量机 支持向量回归机 |
| 文章编号： | 1001-4977(2006)07-0711-04 |
| 收稿时间： | 2005-08-10 |
| 修稿时间： | 2006-04-14 |
Strength of Gray Cast Iron Prediction Model Based on Support Vector Machine |
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| GONG Yan-bing,CHEN Sen-fa.Strength of Gray Cast Iron Prediction Model Based on Support Vector Machine[J].Foundry,2006,55(7):711-714. |
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| Authors: | GONG Yan-bing CHEN Sen-fa |
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| Affiliation: | Institute of Systems Engineering, Southeast University, Nanjing 210096, China |
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| Abstract: | On the basis of the experimental data of microstructure and strength for gray cast iron with high carbon equivalent,a model of support vector machine for gray cast iron prediction was established.Comparing with the models based on multiple statistic analysis,generalized regress-ion neural network or adapted fuzzy neural network model,it shows better learning precision and generalization. |
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| Keywords: | gray cast iron support vector machine support vector regression machine |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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