Using the Robust Principal Component Analysis to Identify Incorrect Aerological Data

被引：0
|
作者：
A. M. Kozin
A. D. Lykov
I. A. Vyazankin
A. S. Vyazankin
机构：
[1] Central Aerological Observatory,
[2] Sechenov First Moscow State Medical University,undefined
来源：
Russian Meteorology and Hydrology | 2021年 / 46卷
关键词：
aerological data; geopotential height; outliers; machine learning; Robust Principal Component Analysis (RPCA);
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：631 / 639
页数：8
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