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Inclination Errors Evaluation of Planar Lines with a Chaos Optimization

机译:倾斜误差使用混沌优化的平面线评估

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To improve inclination error evaluation of planar lines, chaos optimization is proposed to evaluate the minimum zone error in this paper. The evolutional optimum model and the calculation process are introduced. By using the properties of ergodicity, stochastic property, and "regularity" of chaos, the efficiency of chaos optimization algorithm (COA) is much higher than some stochastic algorithms such as simulated anneal algorithm (SAA) and genetic algorithm (GA) when COA is used to a kind of continuous problems. The chaos optimization algorithm can improve the efficiency of searching in the whole field by gradually shrinking the area of optimization variable. Finally, the control experiment results evaluated by different method such as the Least Square, Simplex search, Powell optimum methods and GA, indicate that the proposed method does provide better accuracy on inclination error evaluation.
机译:为了改善平面线的倾斜误差评估,提出了混沌优化来评估本文中的最小区域误差。 引入了进化最佳模型和计算过程。 通过使用混沌的ergodicity,随机性能和“规律性”的性质,COA是COA的模拟退火算法(SAA)和遗传算法(GA)的混沌优化算法(COA)的效率远高于一些随机算法(SAA)和遗传算法(GA) 曾经是一种持续的问题。 混沌优化算法可以通过逐渐缩小优化变量来提高整个场中搜索效率。 最后,通过不同的方法评估的控制实验结果,例如最小二乘,单纯x搜索,鲍威尔最佳方法和Ga,表明所提出的方法在倾斜误差评估上提供更好的准确性。

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