| PSO-SOM分类判别研究及其应用 |
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| 引用本文： | 涂晓芝,颜学峰,钱锋.PSO-SOM分类判别研究及其应用[J].高技术通讯,2006,16(10):1014-1018. |
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| 作者姓名： | 涂晓芝 颜学峰 钱锋 |
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| 作者单位： | 华东理工大学自动化研究所,上海,200237;华东理工大学自动化研究所,上海,200237;华东理工大学自动化研究所,上海,200237 |
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| 基金项目： | 国家自然科学基金
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教育部科学技术研究重点项目
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上海市青年科技启明星计划 |
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| 摘 要： | 针对网络初始权矢量选取的不确定性问题,提出了粒子群优化-自组织映射(PSO-SOM)算法,利用PSO算法优化SOM网络的初始权矢量,进而进行分类.将提出的方法用于基因表达数据的分类判别中,使得SOM网络的误差平方和大大下降,提高了网络的分类精度,表明PSO-SOM算法用于数据的分类判别是切实有效的.
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| 关 键 词： | 自组织映射网络 微粒群算法 分类判别 基因表达数据 |
| 收稿时间： | 2005-11-01 |
| 修稿时间： | 2005年11月1日 |
Research on clustering analysis using PSO-SOM algorithm and its application |
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| Tu Xiaozhi,Yan Xuefeng,Qian Feng.Research on clustering analysis using PSO-SOM algorithm and its application[J].High Technology Letters,2006,16(10):1014-1018. |
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| Authors: | Tu Xiaozhi Yan Xuefeng Qian Feng |
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| Affiliation: | Research Institute of Automation, East China University of Science and Technology, Shanghai 200237 |
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| Abstract: | To solve the problem of uncertainty in the selection of SOM (self-organizing map) networks' initial weights,a PSO (particle swarm optimization)-SOM algorithm was proposed.First the PSO algorithm was used to optimize the initial weight vectors of SOM networks,and then the data were clustered by SOM networks.Finally the proposed method was applied to clustering analysis of gene expression data,and the results showed that the sum of squared errors was reduced by using the PSO-SOM algorithm,also the precision of clustering is improved.It is concluded that the PSO-SOM algo- rithm is efficient to clustering analysis of high dimensional data. |
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| Keywords: | SOM networks PSO algorithms clustering analysis gene expression data |
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