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首页> 外文期刊>Journal of Applied Geophysics >Insights on surface wave dispersion and HVSR: Joint analysis via Pareto optimality
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Insights on surface wave dispersion and HVSR: Joint analysis via Pareto optimality

机译:关于表面波色散和HVSR的见解:通过帕累托最优进行联合分析

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摘要

Surface Wave (SW) dispersion and Horizontal-to-Vertical Spectral Ratio (HVSR) are known as tools able to provide possibly complementary information useful to depict the vertical shear-wave velocity profile. Their joint analysis might then be able to overcome the limits which inevitably affect such methodologies when they are singularly considered. When a problem involves the optimization (i.e. the inversion) of two or more objectives, the standard practice is represented by a normalized summation able to account for the typically different nature and magnitude of the considered phenomena (thus objective functions). This way, a single cost function is obtained and the optimization problem is performed through standard solvers. This approach is often problematic not only because of the mathematically and physically inelegant summation of quantities with different magnitudes and units of measurements. The critical point is indeed represented by the inaccurate performances necessarily obtained while dealing with problems characterized by several local minima and the impossibility of a rigorous assessment of the goodness and meaning of the final result. In the present paper joint analysis of both synthetic and field SW dispersion curves and HVSR datasets is performed via the Pareto front analysis. Results show the relevance of Pareto's criterion not only as ranking system to proceed in heuristic optimization (Evolutionary Algorithms) but also as a tool able to provide some insights about the characteristics of the analyzed signals and the overall congruency of data interpretation and inversion. Possible asymmetry of the final Pareto front models is discussed in the light of relative non-uniqueness of the two considered objective functions.
机译:表面波(SW)色散和水平与垂直光谱之比(HVSR)被称为能够提供可能的补充信息的工具,这些信息可用于描述垂直剪切波速度分布。然后,他们的联合分析也许能够克服单方面考虑时不可避免地影响此类方法的限制。当一个问题涉及两个或多个目标的优化(即反演)时,标准做法以归一化的总和表示,该总和能够说明所考虑现象(因此是目标函数)的通常不同的性质和大小。这样,可以获得单个成本函数,并通过标准求解器执行优化问题。这种方法通常是有问题的,不仅因为在数学上和物理上对具有不同幅度和测量单位的量的求和不佳。关键点实际上是在处理一些以局部极小值为特征的问题以及无法对最终结果的优缺点进行严格评估的过程中必然获得的不准确表现所代表的。在本文中,通过帕累托锋分析对合成和野外SW频散曲线以及HVSR数据集进行联合分析。结果表明,帕累托准则不仅作为在启发式优化中进行的排名系统(进化算法),而且作为能够提供有关分析信号的特征以及数据解释和反演的整体一致性的工具的相关性。根据两个考虑的目标函数的相对非唯一性,讨论了最终的Pareto前沿模型的可能不对称性。

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