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dc.contributor.authorAnglada, Eva
dc.contributor.authorMartinez-Jimenez, Laura
dc.contributor.authorGarmendia, Iñaki
dc.date.accessioned2017-06-27T11:25:56Z
dc.date.available2017-06-27T11:25:56Z
dc.date.issued2017-05-24
dc.identifier.citationANGLADA, Eva; MARTINEZ-JIMENEZ, Laura; GARMENDIA, Iñaki. Performance of gradient-based solutions vs genetic algorithms in the correlation of thermal mathematical models of spacecrafts. International Journal of Aerospace Engineering, Vol. 2017 (2017), May, Article ID 7683457, 12 pages. https://doi.org/10.1155/2017/7683457en
dc.identifier.issn1687-5966en
dc.identifier.urihttp://hdl.handle.net/11556/406
dc.description.abstractThe correlation of the thermal mathematical models (TMMs) of spacecrafts with the results of the thermal test is a demanding task in terms of time and effort. Theoretically, it can be automatized by means of optimization techniques, although this is a challenging task. Previous studies have shown the ability of genetic algorithms to perform this task in several cases, although some limitations have been detected. In addition, gradient-based methods, although also presenting some limitations, have provided good solutions in other technical fields. For this reason, the performance of genetic algorithms and gradient-based methods in the correlation of TMMs is discussed in this paper to compare the pros and cons of them. The case of study used in the comparison is a real space instrument flown on board the International Space Station.en
dc.language.isoengen
dc.publisherHINDAWI LTD, ADAM HOUSE, 3RD FLR, 1 FITZROY SQ, LONDON, W1T 5HF, ENGLANDen
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titlePerformance of Gradient-Based Solutions versus Genetic Algorithms in the Correlation of Thermal Mathematical Models of Spacecraftsen
dc.typearticleen
dc.identifier.doi10.1155/2017/7683457en
dc.isiYesen
dc.rights.accessRightsopenAccessen
dc.subject.keywordsThermal Mathematical Modelen
dc.subject.keywordsSpaceen
dc.subject.keywordsCorrelationen
dc.subject.keywordsModel adjustmenten
dc.subject.keywordsOptimizationen
dc.subject.keywordsGradient-Based solutionsen
dc.subject.keywordsGenetic algorithmsen
dc.journal.titleInternational Journal of Aerospace Engineeringen
dc.page.final12en
dc.page.initial1en
dc.volume.number2017en


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