Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1171796
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dc.contributor.authorLUIZ, A. J. B.
dc.contributor.authorSILVA, F. A. M. da
dc.date.accessioned2025-01-21T12:47:18Z-
dc.date.available2025-01-21T12:47:18Z-
dc.date.created2025-01-21
dc.date.issued2024
dc.identifier.citationSigmae, v. 12, n. 3, p. 213-223, 2023. Special issue: 67th RBRAS and 20th SEAGRO.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1171796-
dc.descriptionAbstract: The use of simulation models is increasingly frequent in research. The greater capacity, both in memory and processing, as well as the great availability, accessibility and amount of data collected and stored, induces and sometimes makes the use of this tool mandatory. On the other hand, when calibrated, the simulation models allow the realization, in seconds and at almost zero cost, of countless estimates of future behavior, in the most different scenarios, which, otherwise, would require a lot of time and resources to be obtained. Crop growth models and climate models are among the most widespread and used in agricultural research. Some metrics have been frequently used by users of these models to assess their efficiency. However, the best techniques are not always employed. In this work, the simulation results of air and soil temperature data were analyzed by two different models: ETA-HADGEM and STICS, respectively. The metrics usually indicated: EF (modelling efficiency) and RMSE (root mean square error), were compared with results of regression analysis and sign test for bias. The introduction of bias correction was also applied and interpreted. It is concluded that the metrics, if used in isolation and without in-depth analysis of the characteristics of the simulated variables, may result in a misinterpretation of the efficiency of the models.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectSTICS
dc.subjectETA-HADGEM
dc.subjectRegression model
dc.subjectSign test
dc.titleCare in the evaluation of simulation models.
dc.typeArtigo de periódico
dc.subject.thesagroModelo de Simulação
dc.subject.thesagroClimatologia
dc.subject.thesagroTemperatura do Solo
dc.subject.nalthesaurusClimate models
dc.subject.nalthesaurusSimulation models
dc.subject.nalthesaurusRegression analysis
dc.subject.nalthesaurusbiaseng
riaa.ainfo.id1171796
riaa.ainfo.lastupdate2025-01-21
dc.contributor.institutionALFREDO JOSE BARRETO LUIZ, CNPMA; FERNANDO ANTONIO MACENA DA SILVA, CPAC.
Aparece nas coleções:Artigo em periódico indexado (CNPMA)

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