| 基于聚类和主成分分析的神经网络预测模型 |
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| 引用本文： | 林树宽,张冬岩,李文贤,张天成,张一飞. 基于聚类和主成分分析的神经网络预测模型[J]. 小型微型计算机系统, 2005, 26(12): 2160-2163 |
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| 作者姓名： | 林树宽 张冬岩 李文贤 张天成 张一飞 |
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| 作者单位： | 东北大学,信息学院,辽宁,沈阳,110004 |
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| 基金项目： | 沈阳市科委科技项目（1041036-1-06-07）资助. |
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| 摘 要： | 提出一种基于聚类和主成分分析的神经网络模型,用于高炉运行指标的实时预测.首先采用谱系聚类将特性分散的样本划分成不同的子类,然后采用主成分分析方法对影响目标数据的众多变量进行降维处理,在此基础上,构建了高炉运行指标的神经网络预测模型,大大改善了预报的精度和效率.通过对采集的高炉数据进行测试,表明本文提出方法的有效性.
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| 关 键 词： | 聚类 主成分分析 神经网络模型 |
| 文章编号： | 1000-1220（2005）12-2160-04 |
| 收稿时间： | 2004-12-07 |
| 修稿时间： | 2004-12-07 |
Neural Network Forecasting Model Based on Clustering and Principle Components Analysis |
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| LIN Shu-kuan,ZHANG Dong-yan,LI Wen-xian,ZHANG Tian-chen,ZHANG Yi-fei. Neural Network Forecasting Model Based on Clustering and Principle Components Analysis[J]. Mini-micro Systems, 2005, 26(12): 2160-2163 |
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| Authors: | LIN Shu-kuan ZHANG Dong-yan LI Wen-xian ZHANG Tian-chen ZHANG Yi-fei |
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| Affiliation: | School of Information Science and Engineering, Northeastern University, Shenyang 110004, China |
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| Abstract: | Presents a neural network prediction model based on clustering and principle components analysis(PCA),which is applied to real-time prediction of economic-technical indexes in blast furnace.The proposed method divides samples which have characteristic of decentralization into different sub-classes with the aid of pedigree clustering,and uses principle components analysis method to reduce the dimensionality of the feature space,and then builds neural network forecasting model.The experiments show that the proposed method is efficient. |
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| Keywords: | clustering principle components analysis neural network model |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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