| 新型并行遗传算法及其在参数估计中的应用 |
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| 引用本文： | 孙晓云,高鑫,王鹏.新型并行遗传算法及其在参数估计中的应用[J].计算机工程与应用,2005,41(19):50-52. |
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| 作者姓名： | 孙晓云 高鑫 王鹏 |
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| 作者单位： | 西安科技大学通信学院,西安,710047;西北电网有限公司调度通信中心,西安,710048 |
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| 摘 要： | 基于极大似然法的参数估计实质上是一个复杂的非线性优化问题,传统的优化方法计算效率较低且容易陷入局部极值。该文将单纯形法与并行遗传算法相结合,提出了一种新的并行遗传算法,可以有效地防止搜索过程中的早熟现象。应用于系统初始状态未知时的参数估计问题,获得了满意的结果。
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| 关 键 词： | 初始状态 极大似然法 单纯形法 并行遗传算法 |
| 文章编号： | 1002-8331-(2005)19-0050-03 |
A New Parallel Genetic Algorithm and its Application to Parameter Estimation |
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| Sun Xiaoyun,Gao Xin,Wang Peng.A New Parallel Genetic Algorithm and its Application to Parameter Estimation[J].Computer Engineering and Applications,2005,41(19):50-52. |
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| Authors: | Sun Xiaoyun Gao Xin Wang Peng |
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| Affiliation: | Sun Xiaoyun1 Gao Xin2 Wang Peng21 |
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| Abstract: | The parameter estimation based on the maximum likelihood method is a complicated nonlinear optimization problem actually.The traditional optimization algorithms are apt to be trapped into local minima,and the computation efficiencies are quite low.In this paper,a new parallel genetic algorithm combining the simplex method with the parallel genetic algorithm is proposed,which can prevent premature convergence effectively and improve the estimation precision and computation efficiency.The proposed algorithm is applied to the parameter estimation problem with unknown initial states of system and satisfactory results are obtained. |
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| Keywords: | initial state maximum likelihood simplex method parallel genetic algorithm |
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