Publication
Fractional Dynamic Fitness Functions for GA-based Circuit Design
| dc.contributor.author | Reis, Cecília | |
| dc.contributor.author | Tenreiro Machado, J. A. | |
| dc.contributor.author | Cunha, J. Boaventura | |
| dc.date.accessioned | 2019-03-27T15:52:56Z | |
| dc.date.available | 2019-03-27T15:52:56Z | |
| dc.date.issued | 2005-06 | |
| dc.description.abstract | This paper proposes and analyses the performance of a Genetic Algorithm (GA) using two new concepts, namely a static fitness function including a discontinuity measure and a fractional-order dynamic fitness function. The GA is adopted for the synthesis of combinational logic circuits. In both cases, experiments reveal superior results in terms of speed and convergence to achieve a solution. | pt_PT |
| dc.description.version | N/A | pt_PT |
| dc.identifier.doi | 10.1145/1068009.1068264 | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/13169 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | Fractional calculus | pt_PT |
| dc.subject | Genetic algorithms | pt_PT |
| dc.subject | Logic circuit design | pt_PT |
| dc.title | Fractional Dynamic Fitness Functions for GA-based Circuit Design | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Washington, D. C. USA | pt_PT |
| oaire.citation.endPage | 4 | pt_PT |
| oaire.citation.startPage | 1 | pt_PT |
| oaire.citation.title | Gecco 2005 | pt_PT |
| person.familyName | Reis | |
| person.familyName | Tenreiro Machado | |
| person.givenName | Cecília | |
| person.givenName | J. A. | |
| person.identifier.ciencia-id | 7A18-4935-5B29 | |
| person.identifier.orcid | 0000-0001-6131-4677 | |
| person.identifier.orcid | 0000-0003-4274-4879 | |
| person.identifier.rid | M-2173-2013 | |
| person.identifier.scopus-author-id | 55989030100 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
| relation.isAuthorOfPublication | 8128af5d-07d3-4b24-944d-30fde21ae59b | |
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| relation.isAuthorOfPublication.latestForDiscovery | 8128af5d-07d3-4b24-944d-30fde21ae59b |
