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Application of Statistical Methods on Automated Recognition of Solar Activity Phenomena and Analysis of Their Correlation

Published online by Cambridge University Press:  01 July 2015

Ganghua Lin
Ganghua Lin*
Affiliation:
Key Laboratory of Solar Activity, Chinese Academy of Sciences National Astronomical Observatories, Chinese Academy of Sciences Datun Rd.20A, Chaoyang District, Beijing, China email: [email protected]
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Abstract

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The recent immense volume of observation data has urged us to recognize solar features and to analyze their correlation with automation methods, and many of these automation methods are closely related to statistical methods. Author investigations the extensive literatures to sum up the function of statistical methods and their advantages in recognizing automatically solar features and analyzing their correlation. The review lists the results and summarizes conclusions of the investigations. The results and conclusions will be helpful to promote the further automation processing.

Keywords

solar featurerecognitionautomationmethods: data analysisstatistics
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 10 , Symposium S306: Statistical Challenges in 21st Century Cosmology , May 2014 , pp. 313 - 315
Copyright
Copyright © International Astronomical Union 2015 

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