| 非线性最小二乘估计的遗传算法 |
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| 引用本文： | 田玉刚,王新洲,花向红.非线性最小二乘估计的遗传算法[J].测绘工程,2004,13(4):6-8. |
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| 作者姓名： | 田玉刚 王新洲 花向红 |
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| 作者单位： | 北京师范大学,资源学院,北京,100875;武汉大学,测绘学院,湖北,武汉,430079 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | 探讨了用遗传算法进行非线性模型参数估计的可能性,设计了非线性最小二乘估计的遗传算法,并用实例验证了该算法的有效性.通过比较该算法与其它算法的结果,得出了一些具有参考价值的结论.
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| 关 键 词： | 非线性最小二乘估计 遗传算法 |
| 文章编号： | 1006-7949(2004)04-0006-03 |
| 修稿时间： | 2004年5月25日 |
Genetic algorithms based on nonlinear least squares estimation |
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| TIAN Yu-gang,WANG Xin-zhou,HUA Xiang-hong.Genetic algorithms based on nonlinear least squares estimation[J].Engineering of Surveying and Mapping,2004,13(4):6-8. |
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| Authors: | TIAN Yu-gang WANG Xin-zhou HUA Xiang-hong |
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| Institution: | TIAN Yu-gang1,WANG Xin-zhou2,HUA Xiang-hong2 |
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| Abstract: | Genetic algorithms (GA) are stochastic search methods that mimic the metaphor of natural biological evolution. It operates on a population of potential solutions of the problem applying the principle of survival of the fittest to produce better and better approximations to a solution. At each generation, a new set of approximations is created by the process of selecting individuals according to their level of fitness in the problem domain and breeding them together using operators borrowed from natural genetics. This process leads to the evolution of populations of individuals that are better suited to their environment than the individuals that they were created from, just as in natural adaptation. In this paper, a new genetic algorithm based on nonlinear least squares estimation is designed) and then an example is used to validate the validity of the algorithm) at last, some conclusions are obtained by comparing the outcome acquired by this algorithm with the results of otber algorithms. |
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| Keywords: | nonlinear least squares estimation) genetic algorithm |
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