Finding sets of acceptable solutions with a genetic algorithm with application to surface wave group dispersion in Europe
Finding sets of acceptable solutions with a genetic algorithm with application to surface wave group dispersion in Europe
复制标题
使用遗传算法寻找可接受的解决方案集，并将其应用于欧洲的表面波群色散
DOI：
10.1029/94gl02635
复制
发表时间：
1994
影响因子：
5.2
通讯作者：
R. Snieder
中科院分区：
文献类型：
--
作者：
A. Lomax;R. Snieder
我们讨论了使用遗传算法（GA）反演数据为许多可接受的解决方案，相反，反演一个单一的，“最佳”的解决方案。遗传算法是一种直接搜索方法，它不需要线性化的前向问题或启动模型，它可以应用于一个非常大的模式！空间因此，需要更少的假设和更大范围的解决方案进行检查比许多其他反演方法。我们应用遗传算法的基本瑞利锡永估计的路径横跨中欧和东欧平台，以确定“平均”，分层S速度模型分别为每个地区。GA的使用允许相同的模型参数化和广泛的参数搜索范围被用于两个区域。可接受的解决方案的分散显示莫霍面周围的速度-深度权衡，表示反演的深度分辨率，并显示上地幔，S速度估计的不确定性。结果表明，较厚的地壳和高达0.3公里/秒（7%）高的S波速度在上100公里的地幔下的老东欧平台比中欧解释的数据集的差异。
We discuss the use of a genetic algorithm (GA) to invert data for many acceptable solutions, in contrast to inversion for a single, "optimum" solution. The GA is a directed search method which does not need linearization of the forward problem or a starting model, and it can be applied with a very large mode!-space. Consequently, fewer assumptions are required and a greater range of solutions is examined than with many other inversion methods. We apply the GA to fundamental Rayleigh group disper- sion estimates for paths across Central Europe and across the East European Platform to determine "average", layered S velocity models separately for each region. The use of the GA allows an identical model parameterization and broad parameter search range to be used for both regions. The scatter of acceptable solutions shows velocity-depth trade-offs around the Moho, indicates the depth resolution of the inversion, and shows the uncertainty in upper mantle, S velocity estimates. The results indicate that a thicker crust and up to 0.3 km/sec (7%) higher S wave velocities in the upper 100 km of the mantle under the older East European Platform than under Central Europe explain most of the differences in the data sets.