| 一种组合最小二乘支持向量机的研究及其应用 |
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| 引用本文： | 秦永宽.一种组合最小二乘支持向量机的研究及其应用[J].现代测绘,2011,34(5):7-10. |
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| 作者姓名： | 秦永宽 |
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| 作者单位： | 无锡市测绘院有限责任公司,江苏无锡,214031 |
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| 摘 要： | 将统计学习理论和LS-SVM用于变形分析预报,采用小生境遗传算法与交叉验证法相结合进行LS-SVM参数的选取,并用参数优选后的LS-SVM与混沌理论相结合对变形监测数据进行建模预测,并与BP和RBF两种神经网络的预测结果进行了比较分析。实例表明,基于组合LS-SVM的变形数据预报模型具有良好的效果。
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| 关 键 词： | 混沌理论 最小二乘支持向量机 变形分析 小生境遗传算法 |
Research on A Combined Least Squares Support Vector Machine and Its Application |
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| QIN Yong-kuan.Research on A Combined Least Squares Support Vector Machine and Its Application[J].Modern Surveying and Mapping,2011,34(5):7-10. |
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| Authors: | QIN Yong-kuan |
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| Institution: | QIN Yong-kuan (Wuxi Surveying & Mapping Institute Co.,Ltd.,Wuxi Jiangsu 214000,China) |
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| Abstract: | This paper researched deformation analysis based on statistical learing theory(SLT) and LS-SVM.First,a new optimization algorithm is proposed based on Niche Genetic Algorithm and Cross-validation,then the combined model of LS-SVM and Chaos theory is used to analyze the deformation data and also compared with BP and RBF neural network.The results show that the prediction model has a good effect. |
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| Keywords: | chaos theory LS-SVM deformation analysis NGA |
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