We address the relation between local amplification and site‐condition indicators derived from in situ geophysical surveys for the estimation of the VS profile, and single‐station recordings processed with horizontal‐to‐vertical spectral ratio technique. Site‐condition indicators, or proxies (e.g., VS30⁠), aim at “summarizing” the description of the local geophysical structure, with a focus on its relation to site amplification.The premise for our work was the compilation of two companion databases: one of soil condition proxies and the other of empirically derived Fourier amplification functions, for Swiss and Japanese stations.We investigated the connection between these two datasets, at first, with a systematic set of regressions correlating each proxy to amplification factors within the frequency band 0.5–20 Hz, second, with a neural network (NN) structure predicting site amplification from proxies.The regression analyses showed that, generally, site‐condition parameters (SCPs) bear a better correlation with amplification within 1.7–6.7 Hz; the “best” indicators are the frequency‐dependent quarter‐wavelength (QWL) velocity and, among scalar parameters, VS30⁠, the bedrock depth, and f0⁠. Collating Swiss and Japanese datasets, the trend of variation of amplification with respect to most proxies is similar. Finally, we evaluated the prediction performance of various combinations of SCPs, for local amplification, using a NN. To attain a database large enough to constrain the estimation of the network parameters, we merged Swiss and Japanese stations into a single training and validation dataset, motivated by the similarities observed in the regression analyses. The outcome we obtained from the NN is encouraging and consistent with the results of the regressions; SCPs with higher correlation to amplification provide a better forecast of the latter (particularly within 1.7–6.7 Hz). More complete input information, such as QWL parameters (velocity, impedance contrast), or extended ensembles of scalar proxies (particularly, including f0⁠), offer a better estimation of local amplification.

中文翻译：

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关于经验放大与瑞士和日本测得的代理之间的关系：系统回归分析和放大的神经网络预测

我们处理了局部放大和现场条件指标之间的关系，这些指标是从现场地球物理勘测中得出的，用于估算VS剖面，以及使用水平-垂直频谱比技术处理的单站记录。现场条件指标或代理（例如VS30⁠）旨在“总结”本地地球物理结构的描述，重点在于其与站点放大的关系。我们工作的前提是汇编两个配套数据库：对于瑞士和日本电台，其中一个是土壤条件代理，另一个是根据经验推导的傅里叶放大函数。首先，我们研究了这两个数据集之间的联系，并进行了系统的回归分析，将每个代理与频段0.5内的放大因子相关联–20 Hz，秒，回归分析表明，一般而言，场所条件参数（SCP）与1.7-6.7 Hz范围内的扩增具有更好的相关性；回归分析表明，场所条件参数（SCP）与扩增之间的相关性更好。“最佳”指标是频率相关的四分之一波长（QWL）速度，以及标量参数中的VS30⁠，基岩深度和f0⁠。比较瑞士和日本的数据集，相对于大多数代理而言，扩增的变化趋势相似。最后，我们使用NN对局部放大的SCP的各种组合的预测性能进行了评估。为了获得足够大的数据库来限制网络参数的估计，我们将瑞士和日本的电台合并为一个训练和验证数据集，其动机是在回归分析中观察到的相似之处。我们从神经网络获得的结果令人鼓舞，并且与回归结果一致。与放大相关性更高的SCP对后者的预测更好（尤其是在1.7–6.7 Hz范围内）。更完整的输入信息，例如QWL参数（速度，阻抗对比）或标量代理的扩展集合（尤其是包括f0？），可以更好地估计局部放大。