2014-12-222014-04-08JORGE, Carlos Antônio Campos. Algoritmo evolutivo multi-objetivo de tabelas para seleção de variáveis em calibração multivariada. 2014. 68 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2014.http://repositorio.bc.ufg.br/tede/handle/tede/3813This work proposes the use of a multi-objective evolutionary algorithm that makes use of subsets stored in a data structure called table in which the best individuals from each objective considered are preserved. This approach is compared in this work with the traditional mono-objective evolutionary algorithm (GA), classical algorithms (PLS and SPA) and another classic multi-objective algorithm (NSGA-II). As a case study, a multivariate calibration problem is presented which involves the prediction of protein concentration in samples of whole wheat from the spectrophotometric measurements. The results showed that the proposed formulation has a smaller prediction error when compared to the mono-objective formulation and with a lower number of variables. Finally,astudyofnoisesensitivityobtainedbythemulti-objectiveformulationshoweda better resultwhen compared tothe other classical algorithmforvariable selection.application/pdfAcesso AbertoSeleção de variáveisAlgoritmos evolutivosCalibraçãoAlgoritmos multi-objetivosMultivariate calibrationVariable selectionEvolutionary algorithmsMulti-objective algorithmsCIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAODissertação