| 基于改进PSO-SMO的模型参数辨识及应用 |
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| 引用本文： | 刘林,王刚,杨永洪,翟永杰. 基于改进PSO-SMO的模型参数辨识及应用[J]. 信息技术, 2011, 0(7): 121-124,129 |
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| 作者姓名： | 刘林 王刚 杨永洪 翟永杰 |
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| 作者单位： | 1. 华北电力大学自动化系,保定,071003
2. 二滩水力发电厂,攀枝花,617000 |
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| 摘 要： | 目前,大多数智能辨识方法只考虑辨识系统的输出值,不能辨识模型的参数.对此,研究了基于线性核函数支持向量机的辨识算法,对模型参数和输出同时进行辨识.在此基础上,采用改进的PSO-SMO算法以提高辨识速度和精度.将该方法用于ARX模型和长期预测模型的参数辨识中,结果表明,该算法比其他算法具有更高的准确性.
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| 关 键 词： | PSO-SMO 参数辨识 ARX模型 长期预测模型 |
Model parameters identification and application based on improved PSO-SMO |
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| LIU Lin,WANG Gang,YANG Yong-hong,ZHAI Yong-jie. Model parameters identification and application based on improved PSO-SMO[J]. Information Technology, 2011, 0(7): 121-124,129 |
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| Authors: | LIU Lin WANG Gang YANG Yong-hong ZHAI Yong-jie |
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| Affiliation: | 1(1.Department of Automation,North China Electric Power University,Baoding 071003,China; 2.Ertan Hydropower Station,Panzhihua 617000,China) |
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| Abstract: | At present,the most intelligent identification methods can only identify the output of a system,instead of the model parameters.For this problem,this paper studied the identification algorithm of SVM based on linear kernel function.In the concrete realization,it used the improved PSO-SMO algorithm to improve identification speed and precision.Using this method to identify the parameters of ARX model and long-term prediction model,the simulation results show that this algorithm has a higher accuracy than that of other method. |
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| Keywords: | PSO-SMO parameters identification ARX model long-term prediction model |
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