Scalable Multivariate Time-Series Models for Climate Informatics

被引：0

作者：

Liu, Yan ^{[1
]}

机构：

[1] Univ So Calif, Viterbi Sch Engn Comp Sci Dept, Los Angeles, CA 90095 USA

来源：

COMPUTING IN SCIENCE & ENGINEERING | 2015年 / 17卷 / 06期

基金：

美国国家科学基金会;

关键词：

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Climate data not only have a massive scale but are also of high dimension and complex dependency structures, making the analysis task extremely challenging. Recent advances in machine learning can help researchers tackle a series of problems in climate data analysis, such as climate change attribution, spatiotemporal analysis, and extreme value time-series analysis.

引用

页码：19 / 26

页数：8

共 50 条

[1] Scalable Multivariate Time-Series Models for Climate Informatics
University of Southern California, Los Angeles, United States
Comput. Sci. Eng., 6 (19-26):
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