Anomalous cluster detection in spatiotemporal meteorological fields-Reference-Cited by-同舟云学术

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Anomalous cluster detection in spatiotemporal meteorological fields

Published:2018-12-26 Issue:2 Volume:12 Page:88-100
ISSN:1932-1864
Container-title:Statistical Analysis and Data Mining: The ASA Data Science Journal
language:en
Short-container-title:Stat Anal Data Min: The ASA Data Sci Journal.

Author:

Ramachandra Bharathkumar¹^ORCID,Dutton Benjamin¹,Vatsavai Ranga Raju¹

Affiliation:

1. Department of Computer Science North Carolina State University Raleigh North Carolina

Funder

U.S. Department of Energy

Laboratory Directed Research and Development

Publisher

Wiley

Subject

Computer Science Applications,Information Systems,Analysis

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sam.11398

Reference43 articles.

1. Outlier detection by active learning

2. Outlier Analysis

3. Fast Very Robust Methods for the Detection of Multiple Outliers

4. Mining distance-based outliers in near linear time with randomization and a simple pruning rule

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A hierarchical spline model for correcting and hindcasting temperature data;The Annals of Applied Statistics;2024-06-01

2. Piece‐wise constant cluster modelling of dynamics of upwelling patterns;Expert Systems;2023-09-12

3. On the nature and types of anomalies: a review of deviations in data;International Journal of Data Science and Analytics;2021-08-04

4. Dynamic graph embedding for outlier detection on multiple meteorological time series;PLOS ONE;2021-02-18

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