Completion of a Sparse GLIDER Database Using Multi-iterative Self-Organizing Maps (ITCOMP SOM)
Completion of a Sparse GLIDER Database Using Multi-iterative Self-Organizing Maps (ITCOMP SOM)
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DOI：
10.1016/j.procs.2015.05.496
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发表时间：
2015
影响因子：
1.6
通讯作者：
A. Charantonis;P. Testor;L. Mortier;F. D’Ortenzio;S. Thiria
中科院分区：
文献类型：
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作者：
A. Charantonis;P. Testor;L. Mortier;F. D’Ortenzio;S. Thiria
我们提出了一种名为ITCOMP SOM的新方法，该方法使用迭代自组织映射（SOM）来逐步重建高度相关的多维数据集中的缺失数据。该方法被应用于一个复杂的海洋学数据集的完成，该数据集包含EGO项目的黎凡特之眼实验的滑翔机数据。ITCOMP SOM提供了重建的温度和盐度剖面，与他们采样的物理现象一致。进行了交叉验证测试并验证了该方法，为重建温度剖面提供了0.042°C的均方根误差，为同时重建盐度剖面提供了0.008 PSU的均方根误差。
We present a novel approach named ITCOMP SOM that uses iterative self-organizing maps (SOM) to progressively reconstruct missing data in a highly correlated multidimensional dataset. This method was applied for the completion of a complex oceanographic data-set containing glider data from the EYE of the Levantine experiment of the EGO project. ITCOMP SOM provided reconstructed temperature and salinity profiles that are consistent with the physics of the phenomenon they sampled. A cross-validation test was performed and validated the approach, providing a root mean square error of providing a root mean square error of 0,042 °C for the reconstruction of the temperature profiles and 0,008 PSU for the simultaneous reconstruction of the salinity profiles.