数据挖掘的三维激光扫描参数优化研究

Research on 3D laser scanning parameters optimization of data mining

参数优化准确直接影响三维激光扫描精度,针对当前方法难高精度的拟合三维激光扫描参数值,以降低致三维激光扫描误差为目标,提出了基于数据挖掘的三维激光扫描参数优化方法。首先对三维激光扫描参数之间的关系进行分析,发现参数之间一种强耦合、非线性联系,然后引入数据挖掘中的支持向量回归机对三维激光扫描参数变化关系进行拟合,并引入自适应遗传算法进一步提高三维激光扫描精度,最后采用具体仿真测试对其性能进行综合测试,本文方法可以较好挖掘出出三维激光扫描参数间联系,可以准确确定三维激光扫描参数值,有助于改善三维激光扫描精度,具有一定实际应用价值。

To optimize the parameters of a direct impact on the accuracy of 3D laser scanning precision,in view of the current method to fit the 3D laser scanning parameters with high precision,to reduce the error caused by 3D laser scanning as the goal,put forward the optimization method of 3D laser scanning parameters based on data mining. The relationship between 3D laser scanning parameters were analyzed,and found a strong coupling and nonlinear relationship between parameters,and then introduced the support vector data mining by fitting regression change on 3D laser scanning parameters,and the adaptive genetic algorithm to further improve the precision of 3D laser scanning,finally the comprehensive simulation test was carried out for its performance. This method can better mining 3D laser scanning parameters,accurately determine the 3D laser scanning parameters. It＇s helpful to improve the precision of 3D laser scanning and has certain practical application value.