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《Engineering of Surveying and Mapping》 2004-04
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Genetic algorithms based on nonlinear least squares estimation

TIAN Yu-gang1, WANG Xin-zhou2, HUA Xiang-hong2(1. College of Resource Science & Technology, Beijing Normal University, Beijing 100875, China)2. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China)  
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.
【Fund】: 国家高新技术研究发展计划(863计划)项目(2001AA135081)
【CateGory Index】: P207
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