Presentation 2013-03-15
Prediction of growth of complex networks
Suguru YAGINUMA, Kaori KURODA, Yutaka SHIMADA, Kantaro FUJIWARA, Tohru IKEGUCHI,
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Abstract(in English) In this report, we propose a method to predict growth of a complex network. In our method, first, we transformed a complex network into a time series. Next, we predicted the time series by using a method of nonlinear time series prediction. Then, we reconstructed a complex network from the predicted time series. Finally, we evaluated growth of the predicted networks by comparing them with the real networks. Through numerical simulations, we show that we can predict growth of complex networks with high accuracy using the proposed method.
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Keyword(in English) complex networks / growing networks / nonlinear prediction
Paper # NLP2012-163
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Conference Information
Committee NLP
Conference Date 2013/3/7(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Prediction of growth of complex networks
Sub Title (in English)
Keyword(1) complex networks
Keyword(2) growing networks
Keyword(3) nonlinear prediction
1st Author's Name Suguru YAGINUMA
1st Author's Affiliation Graduate School of Science and Engineering, Saitama University()
2nd Author's Name Kaori KURODA
2nd Author's Affiliation Graduate School of Science and Engineering, Saitama University
3rd Author's Name Yutaka SHIMADA
3rd Author's Affiliation FIRST, Aihara Innovative Mathematical Modelling Project, JST:Institute of Industrial Science, the University of Tokyo
4th Author's Name Kantaro FUJIWARA
4th Author's Affiliation Graduate School of Science and Engineering, Saitama University
5th Author's Name Tohru IKEGUCHI
5th Author's Affiliation Graduate School of Science and Engineering, Saitama University:Saitama University Brain Science Insititute
Date 2013-03-15
Paper # NLP2012-163
Volume (vol) vol.112
Number (no) 487
Page pp.pp.-
#Pages 6
Date of Issue