| 在线稀疏最小二乘支持向量回归机及其应用 |
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| 引用本文： | 赵永平,孙健国. 在线稀疏最小二乘支持向量回归机及其应用[J]. 南京航空航天大学学报(英文版), 2009, 26(4): 280-287 |
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| 作者姓名： | 赵永平 孙健国 |
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| 作者单位： | 南京航空航天大学能源与动力学院,南京,210016,中国;南京航空航天大学能源与动力学院,南京,210016,中国;南京航空航天大学能源与动力学院,南京,210016,中国 |
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| 基金项目： | 国家自然科学基金,the Aeronautical Science Foundation of China |
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| 摘 要： | 提出了一种简单有效的方法——OPLS—SVR来实现在线最小二乘支持向量回归机解的稀疏性。由于稀疏性的实现,在线稀疏最小二乘支持向量回归机的响应时间被大大缩短。此外,为了保证给航空发动机控制器提供可靠、正确的控制信号,提出了一种基于OPLS—SVR的解析余度技术来解决传感器失效和漂移问题。仿真实验表明了该解析余度技术有效且可行。
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| 关 键 词： | 支持向量机 传感器 最小二乘 解析余度 航空发动机 |
ONLINE PARSIMONIOUS LEAST SQUARES SUPPORT VECTOR REGRESSION AND ITS APPLICATION |
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| Zhao Yongping,Sun Jianguo,Wang Jiankang. ONLINE PARSIMONIOUS LEAST SQUARES SUPPORT VECTOR REGRESSION AND ITS APPLICATION[J]. Transactions of Nanjing University of Aeronautics & Astronautics, 2009, 26(4): 280-287 |
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| Authors: | Zhao Yongping Sun Jianguo Wang Jiankang |
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| Abstract: | A simple and effective mechanism is proposed to realize the parsimoniousness of the online least squares support vector regression (LS-SVR), and the approach is called the OPLS-SVR for short.Hence, the response time is curtailed.Besides, an OPLS-SVR based analytical redundancy technique is presented to cope with the sen-sor failure and drift problems to guarantee that the provided signals for the aeroengine controller are correct and acceptable.Experiments on the sensor failure and drift show the effectiveness and the validity of the proposed analytical redundancy. |
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| Keywords: | support vector machines sensors least squares analytical redundancy aeroengines |
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