Calculation of fractional derivatives of noisy data with genetic algorithms

Bibliographic Details
Main Author: Machado, J. A. Tenreiro
Publication Date: 2009
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.22/4314
Summary: This paper addresses the calculation of derivatives of fractional order for non-smooth data. The noise is avoided by adopting an optimization formulation using genetic algorithms (GA). Given the flexibility of the evolutionary schemes, a hierarchical GA composed by a series of two GAs, each one with a distinct fitness function, is established.
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spelling Calculation of fractional derivatives of noisy data with genetic algorithmsFractional derivativesFractional calculusGenetic algorithmsNumerical differentiationThis paper addresses the calculation of derivatives of fractional order for non-smooth data. The noise is avoided by adopting an optimization formulation using genetic algorithms (GA). Given the flexibility of the evolutionary schemes, a hierarchical GA composed by a series of two GAs, each one with a distinct fitness function, is established.SpringerREPOSITÓRIO P.PORTOMachado, J. A. Tenreiro2014-04-04T11:35:48Z20092009-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/4314eng0924-090X1573-269X10.1007/s11071-008-9436-1info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-04-02T03:01:08Zoai:recipp.ipp.pt:10400.22/4314Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T00:34:34.322651Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Calculation of fractional derivatives of noisy data with genetic algorithms
title Calculation of fractional derivatives of noisy data with genetic algorithms
spellingShingle Calculation of fractional derivatives of noisy data with genetic algorithms
Machado, J. A. Tenreiro
Fractional derivatives
Fractional calculus
Genetic algorithms
Numerical differentiation
title_short Calculation of fractional derivatives of noisy data with genetic algorithms
title_full Calculation of fractional derivatives of noisy data with genetic algorithms
title_fullStr Calculation of fractional derivatives of noisy data with genetic algorithms
title_full_unstemmed Calculation of fractional derivatives of noisy data with genetic algorithms
title_sort Calculation of fractional derivatives of noisy data with genetic algorithms
author Machado, J. A. Tenreiro
author_facet Machado, J. A. Tenreiro
author_role author
dc.contributor.none.fl_str_mv REPOSITÓRIO P.PORTO
dc.contributor.author.fl_str_mv Machado, J. A. Tenreiro
dc.subject.por.fl_str_mv Fractional derivatives
Fractional calculus
Genetic algorithms
Numerical differentiation
topic Fractional derivatives
Fractional calculus
Genetic algorithms
Numerical differentiation
description This paper addresses the calculation of derivatives of fractional order for non-smooth data. The noise is avoided by adopting an optimization formulation using genetic algorithms (GA). Given the flexibility of the evolutionary schemes, a hierarchical GA composed by a series of two GAs, each one with a distinct fitness function, is established.
publishDate 2009
dc.date.none.fl_str_mv 2009
2009-01-01T00:00:00Z
2014-04-04T11:35:48Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/4314
url http://hdl.handle.net/10400.22/4314
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0924-090X
1573-269X
10.1007/s11071-008-9436-1
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eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
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