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非线性回归支持向量机的SMO算法改进

, PP. 125-130

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Abstract:

为了解决非线性数据和非线性函数的回归问题,采用了支持向量机序列最小优化算法.原始序列最小优化(SMO,SequentialMinimalOptimization)算法存在训练速度慢和训练结果不稳定的缺点,为了能加快SMO算法的训练速度和提高训练结果稳定性,通过改进优化乘子更新方法、采用双阈值法、预存核函数、增加停机准则等方法对SMO算法做了改进.仿真实验表明,改进的算法能很好地对非线性数据和非线性函数进行回归,具有比原始SMO算法更快的训练速度和稳定的训练结果.

References

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[12]  王书舟, 伞冶, 张允昌.基于支持向量机改进 SMO 算法的直升机旋翼自转着陆过程建模[J].航空学报, 2009, 30(1): 46-51 Wang Shuzhou, San Ye, Zhang Yunchang.Modeling for landing process of helicopter with rotator self-rotating based on modified SMO algorithm of support vector machine[J].Acta Aeronautica et Astronautica Sinica, 2009, 30(1):46-51(in Chinese)
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[14]  王定成.支持向量机建模预测与控制[M].北京:气象出版社, 2009:48-49 Wang Dingcheng.Prediction and control based on support vector machine modelling[M].Beijing:Meteorological Press, 2009:48-49(in Chinese)
[15]  张浩然, 韩正之.回归支持向量机的改进序列最小优化学习算法[J].软件学报, 2003, 14(12):2006-2013 Zhang Haoran, Han Zhengzhi.An improved sequential minimal optimization learning algorithm for regression support vector machine[J].Journal of Software, 2003, 14(12):2006-2013 (in Chinese)
[16]  刘胜, 李妍妍.自适应GA-SVM参数选择算法研究[J].哈尔滨工程大学学报, 2007, 28(4):398-402 Liu Sheng, Li Yanyan.Parameter selection algorithm for support Vector machines based on adaptive genetic algorithm[J].Journal of Harbin Engineering University, 2007, 28(4):398-402 (in Chinese)
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[18]  董磊, 任章, 李清东.基于SMO-SVR的飞机舵面损伤故障趋势预测[J].北京航空航天大学学报, 2012, 38(10): 1300-1305 Dong Lei, Ren Zhang, Li Qingdong.Fault prediction for aircraft control surface damage based on SMO-SVR[J].Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(10):1300-1305 (in Chinese)
[19]  王书舟, 伞冶, 张允昌.基于支持向量机改进 SMO 算法的直升机旋翼自转着陆过程建模[J].航空学报, 2009, 30(1): 46-51 Wang Shuzhou, San Ye, Zhang Yunchang.Modeling for landing process of helicopter with rotator self-rotating based on modified SMO algorithm of support vector machine[J].Acta Aeronautica et Astronautica Sinica, 2009, 30(1):46-51(in Chinese)
[20]  王定成.支持向量机建模预测与控制[M].北京:气象出版社, 2009:48-49 Wang Dingcheng.Prediction and control based on support vector machine modelling[M].Beijing:Meteorological Press, 2009:48-49(in Chinese)

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