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Multi-fractal Property and Long-Range Correlation of Chaotic Time Series
Deng LH(邓林华)
Source PublicationProceedings - 2016 3rd International Conference on Information Science and Control Engineering, ICISCE 2016
2016-10-31
Pages1361-1365
DOI10.1109/ICISCE.2016.290
Author of SourceLi, SZ; Dai, Y; Cheng, Y
Contribution Rank第1完成单位
Indexed ByEI ; CPCI
Conference Name3rd International Conference on Information Science and Control Engineering, ICISCE 2016
Conference Date2016-07-08
Conference PlaceBeijing, PEOPLES R CHINA
Conference SponsorIEEE; IEEE Comp Soc; Univ Texas San Antonio; Beijing Univ Civil Engn & Architecture; Univ Hull; Xiamen Univ; China Jiliang Univ; Hunan Univ Humanities Sci & Technol; Iwate Prefectural Univ; Univ Amoiensis
KeywordInformation Processing Time Series Analysis Hurst Exponent Multi-fractal Analysis Long-range Correlation
Abstract

The multi-fractal structure and long-range memory reveal the scale invariance of irregular objects in nature, and have been the subject of substantial interest due to the wide range of phenomena associated with many aspects, appearing in several scientific areas. Two quantitative analysis approaches, including multi-fractal analysis and rescaled range analysis, are combined to analyze the magnetic complexity and multi-fractal behavior of solar Ha flare activity. The following prominent results are found: (1) The calculated values of Hurst exponent for solar flare activity lie in between 0.8362 and 0.9420, exhibiting the persistent behavior of long-range correlation, (2) The values of fractal dimension reflect that solar flare activity in the northern hemisphere is more irregular than that in the southern hemisphere and in the whole solar disk, (3) The values of predictability indicator of solar flare activity are larger than 0.5, implying that solar flare activity is predictable and chaotic in nature, (4) The widths of singularity spectra indicate that solar flare activity has multi-fractal behavior and such multi-fractal nature is due to long-range correlation. These findings may be instructive to the physical processes of flare energy storage and dissipation, and to be useful for predicting solar flare eruption. © 2016 IEEE.

Funding ProjectFound of Sichuan University of Science and Engineering[2015RC43] ; National Natural Science Foundation of China (NSFC)[11503082]
Funding OrganizationFound of Sichuan University of Science and Engineering ; National Natural Science Foundation of China (NSFC)
Language英语
Subject Area天文学
MOST Discipline Catalogue理学 ; 理学::天文学
SubtypeProceedings Paper
PublisherInstitute of Electrical and Electronics Engineers (IEEE) Inc.
Publication Place345 E 47TH ST, NEW YORK, NY 10017 USA
ISBN978-1-5090-2535-0
URL查看原文
Archive Date2016-12-30
WOS IDWOS:000390690700280
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Theory & Methods
WOS KeywordSolar-flare Geometries ; Low-dimensional Chaos ; Nonlinear-analysis ; Recurrence Plots ; Index ; Complexity ; Dependence ; Behavior
EI Accession Number20165003107115
EI KeywordsTime Series Analysis
EI Classification Number723.2data Processing And Image Processing - 921mathematics - 922.2mathematical Statistics
Citation statistics
Document Type会议论文
Identifierhttp://ir.ynao.ac.cn/handle/114a53/9797
Collection抚仙湖太阳观测站
Corresponding AuthorDeng LH(邓林华)
AffiliationYunnan Observatories, Chinese Academy of Sciences, Kunming 650011, P.R. China
Recommended Citation
GB/T 7714
Deng LH. Multi-fractal Property and Long-Range Correlation of Chaotic Time Series[C]//Li, SZ; Dai, Y; Cheng, Y. 345 E 47TH ST, NEW YORK, NY 10017 USA:Institute of Electrical and Electronics Engineers (IEEE) Inc.,2016:1361-1365.
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