NDLI: Knowledge discovery based on statistics of MDI Magnetogram

Content Provider	IEEE Xplore Digital Library
Author	Daren Yu Xiaopeng Zhang Jinfu Liu Qiang Wang
Copyright Year	2012
Description	Author affiliation: School of Astronautics, Harbin Institute of Technology, China (Daren Yu; Xiaopeng Zhang; Jinfu Liu; Qiang Wang)
Abstract	Solar flare is one of the most powerful activities, which plays a very important role in daily life and space weather, so it is meaningful to predict solar flare accurately. Now expert system is also the main prediction method, for the nature mechanism of solar flare is unclearly, so prediction is often inaccurate. As the increasing of human expectation to discover the outer space, more and more satellites were sent, especially around the sun, so the number of solar daily observed images is more than 1 TBs and with a very high resolution, so it is particularly important to search solar activities from image information. 11 years of SOHO/MDI Magnetograms are selected which contain more than 70 thousands samples. 35 image features are extracted, three of them are usually used by physicists and others are information from image. Three evaluation methods are used to measure the single feature performance and their relationships, which imply that: 1.Length of neutral line is the most powerful predictor; 2. Predictors of morphology evolution of active regions are all very useful and better than the maximum horizontal gradient which physicists used, but with the analysis of relationships between each other, they all have very strong correlation; 3. Although magnetic field distorted portrayals are less power with solar flare, it play very good quality information complementary with the other better features. Through the statistics of large-scale samples, the relationship of solar image features is more clearly and a more comprehensive collation result of relationship between active region and solar flare is got.
Starting Page	1514
Ending Page	1518
File Size	637713
Page Count	5
File Format	PDF
ISBN	9781467300254
e-ISBN	9781467300247
DOI	10.1109/FSKD.2012.6234089
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Correlation Magnetic resonance imaging solar activity large sample statistics learning Feature extraction Prediction algorithms knowledge discovery Data mining Magnetic fields image feature Expert systems
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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