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Number of results
Journal
2013 | 11 | 6 | 724-739
Article title

Self-similarity principle: the reduced description of randomness

Content
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Languages of publication
EN
Abstracts
EN
A new general fitting method based on the Self-Similar (SS) organization of random sequences is presented. The proposed analytical function helps to fit the response of many complex systems when their recorded data form a self-similar curve. The verified SS principle opens new possibilities for the fitting of economical, meteorological and other complex data when the mathematical model is absent but the reduced description in terms of some universal set of the fitting parameters is necessary. This fitting function is verified on economical (price of a commodity versus time) and weather (the Earth’s mean temperature surface data versus time) and for these nontrivial cases it becomes possible to receive a very good fit of initial data set. The general conditions of application of this fitting method describing the response of many complex systems and the forecast possibilities are discussed.
Publisher

Journal
Year
Volume
11
Issue
6
Pages
724-739
Physical description
Dates
published
1 - 6 - 2013
online
9 - 10 - 2013
Contributors
  • Theoretical Physics Department, Institute of Physics, Kazan Federal University, Kremlevskaya str., 18, 420008, Kazan, Tatarstan, Russian Federation, renigmat@gmail.com
author
  • Dept. of Electrical Engineering, Institute of Engineering of Polytechnic of Porto, Rua Dr. Antonio Bernardino de Almeida, 431, 4200-072, Porto, Portugal, jtm@isep.ipp.pt
author
  • Dept. of Quantitative Methods, ISCTE Business School, Av. das Forças Armadas, 1649-025, Lisbon, Portugal, rui.menezes@iscte.pt
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.-psjd-doi-10_2478_s11534-013-0181-9
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