| SVR的限定记忆在线辨识算法及其应用 |
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| 引用本文： | 徐大平,杨金芳,翟永杰,韩璞.SVR的限定记忆在线辨识算法及其应用[J].动力工程,2005,25(5):680-684. |
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| 作者姓名： | 徐大平 杨金芳 翟永杰 韩璞 |
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| 作者单位： | 华北电力大学,保定,071003 |
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| 基金项目： | 华北电力大学校科研和教改项目 |
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| 摘 要： | 目前,基于支持向量回归的辨识研究虽然涉及领域很广,但基本上都为离线辨识,其原因在于支持向量回归处理大批数据时存在耗时长及内存开销大的问题,不能满足实时计算的要求。针对这个问题提出了基于支持向量回归的限定记忆在线辨识算法,该算法有效地避免了内存开销大的问题,满足了在线辨识实时性的要求。利用该算法对具有动态、时变特性的主汽温系统进行了辨识研究,仿真结果表明:该算法可以获得很好的辨识效果,具有良好的可行性。图6表1参9
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| 关 键 词： | 自动控制技术 在线辨识 支持向量回归 主汽温控制系统 限定记忆 单步预测 |
| 文章编号： | 1000-6761（2005）05-0680-05 |
| 收稿时间： | 2005-03-14 |
| 修稿时间： | 2005-03-142005-07-12 |
An On-line Identification Algorithm Based on SVR's Limited Memory and Its Application |
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| XU Da-ping,YANG Jin-fang,ZHAI Yong-jie,HAN Pu.An On-line Identification Algorithm Based on SVR''''s Limited Memory and Its Application[J].Power Engineering,2005,25(5):680-684. |
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| Authors: | XU Da-ping YANG Jin-fang ZHAI Yong-jie HAN Pu |
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| Affiliation: | North China University of Electric Power, Baoding 071003, China |
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| Abstract: | An on-line identification algorithm based on SVR's (support vector regression) limited memory is being proposed, which can effectively dodge the problem of occupying too large a volume of memory and satisfy the requirements of real time identification. The algorithm has been used for identification studies of fresh steam temperature, which is characterized by its dynamic and time varying behavior. Simulation results show the algorithm to be feasible and sound. Figs 6, table 1 and refs 9. |
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| Keywords: | automatic control technique on-line identification support vector regression fresh steam temperature control system limited memory single-step forecasting |
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