Publication
Calculation of fractional derivatives of noisy data with genetic algorithms
| dc.contributor.author | Machado, J. A. Tenreiro | |
| dc.date.accessioned | 2014-04-04T11:35:48Z | |
| dc.date.available | 2014-04-04T11:35:48Z | |
| dc.date.issued | 2009 | |
| dc.description.abstract | 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. | por |
| dc.identifier.doi | 10.1007/s11071-008-9436-1 | pt_PT |
| dc.identifier.issn | 0924-090X | |
| dc.identifier.issn | 1573-269X | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/4314 | |
| dc.language.iso | eng | por |
| dc.peerreviewed | yes | por |
| dc.publisher | Springer | por |
| dc.relation.ispartofseries | Nonlinear Dynamics; Vol. 57, Issue 1-2 | |
| dc.relation.publisherversion | http://link.springer.com/article/10.1007/s11071-008-9436-1 | por |
| dc.subject | Fractional derivatives | por |
| dc.subject | Fractional calculus | por |
| dc.subject | Genetic algorithms | por |
| dc.subject | Numerical differentiation | por |
| dc.title | Calculation of fractional derivatives of noisy data with genetic algorithms | por |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 260 | por |
| oaire.citation.issue | Issue 1-2 | por |
| oaire.citation.startPage | 253 | por |
| oaire.citation.title | Nonlinear Dynamics | por |
| oaire.citation.volume | Vol. 57 | por |
| person.familyName | Tenreiro Machado | |
| person.givenName | J. A. | |
| person.identifier.ciencia-id | 7A18-4935-5B29 | |
| person.identifier.orcid | 0000-0003-4274-4879 | |
| person.identifier.rid | M-2173-2013 | |
| person.identifier.scopus-author-id | 55989030100 | |
| rcaap.rights | openAccess | por |
| rcaap.type | article | por |
| relation.isAuthorOfPublication | 82cd5c17-07b6-492b-b3e3-ecebdad1254f | |
| relation.isAuthorOfPublication.latestForDiscovery | 82cd5c17-07b6-492b-b3e3-ecebdad1254f |