Human exposure induced by wireless communication systems increasingly draws the public attention. Here, an indoor down-link scenario is concerned and the exposure level is statistically analyzed. The electromagnetic field (EMF) emitted by a WiFi box is measured and electromagnetic dosimetry features are evaluated from the whole-body specific absorption rate as computed with a Finite-Difference Time-Domain (a.k.a. FDTD) code. Due to computational cost, a statistical analysis is performed based on a surrogate model, which is constructed by means of so-called sparse polynomial chaos expansion (PCE), where the inner cross validation (ICV) is used to select the optimal hyperparameters during the model construction and assess the model performance. However, the ICV error is optimized and the model assessment tends to be overly optimistic with small data sets. The method of cross-model validation is used and outer cross validation is carried out for the model assessment. The effects of the data preprocessing are investigated as well. Based on the surrogate model, the global sensitivity of the exposure to input parameters is analyzed from Sobol' indices.

中文翻译：

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基于稀疏多项式混沌展开的室内下行人体暴露代理建模

无线通信系统引起的人体暴露越来越引起公众的关注。在此，关注室内下行链路场景，并对暴露水平进行统计分析。测量 WiFi 盒发射的电磁场 (EMF)，并根据使用有限差分时域 (又名 FDTD) 代码计算的全身比吸收率评估电磁剂量学特征。由于计算成本，基于代理模型进行统计分析，该模型通过所谓的稀疏多项式混沌展开 (PCE) 构建，其中内部交叉验证 (ICV) 用于选择最佳超参数。模型构建和模型性能评估。然而，ICV 误差得到优化，模型评估对于小数据集往往过于乐观。模型评估采用交叉模型验证的方法，并进行外部交叉验证。还研究了数据预处理的影响。基于代理模型，从 Sobol 的指数中分析了对输入参数的暴露的全局敏感性。