| 基于混沌PSO算法优化LS-SVM的惯导系统测试 |
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| 引用本文： | 王成,郝顺义,翁大庆,冯文. 基于混沌PSO算法优化LS-SVM的惯导系统测试[J]. 传感器与微系统, 2011, 30(2): 125-128 |
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| 作者姓名： | 王成 郝顺义 翁大庆 冯文 |
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| 作者单位： | 1. 空军工程大学,工程学院,陕西,西安,710038
2. 中国人民解放军94371部队,装备部,河南,郑州,450046 |
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| 摘 要： | 基于混沌PSO算法优化最小二乘支持向量机(LS-SVM)实现惯导系统初始对准测试.通过小波包分解消除陀螺漂移数据的噪声,获取LS-SVM的训练与测试样本.针对LS-SVM解决大规模数据样本回归问题时所出现的训练时间长、收敛速度慢等缺点,提出了混沌PSO算法优化LS-SVM的模型参数.该方法不仅克服了传统PSO算法早熟、...
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| 关 键 词： | 最小二乘支持向量机 混沌粒子群优化算法 惯导系统 初始对准 |
Monitoring of INS based on chaos PSO algorithm optimization parameters of LS-SVM |
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| WANG Cheng,HAO Shun-yi,WENG Da-qing,FENG Wen. Monitoring of INS based on chaos PSO algorithm optimization parameters of LS-SVM[J]. Transducer and Microsystem Technology, 2011, 30(2): 125-128 |
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| Authors: | WANG Cheng HAO Shun-yi WENG Da-qing FENG Wen |
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| Abstract: | Based on chaos PSO algorithm optimization parameters of LS-SVM,monitoring of INS's initial alignment is realized.Noises in INS's error data are eliminated by wavelet decomposition,learning and testing samples for LS-SVM are also acquired.Aimed at LS-SVM solving large scale data regression led to long training time and slow convergence speed,chaos PSO algorithm optimization parameters of LS-SVM is proposed.The disadvantages of earliness and tending to get into local solution in traditional PSO algorithm are overcomed by this method.It also remarkably improves forecasting ability of LS-SVM.The results of general LS-SVM and GM(1,1) forecasting model is compared with the results of this article,it proves this method has a transparent superior in forecasting precision. |
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| Keywords: | least squares support vector machine(LS-SVM) chaos particle swarm optimization algorithm inertial navigation system(INS) initial alignment |
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