Pesquisa de referências

Forest-genetic method to optimize parameter design of multiresponse experiment

Forest-genetic method to optimize parameter design of multiresponse experiment
Recurso electrónico / Electronic resource
Registro MARC
Tag12Valor
LDR  00000cab a2200000 4500
001  MAP20200037248
003  MAP
005  20220911190417.0
008  201123e20201201esp|||p |0|||b|spa d
040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
084  ‎$a‎922.134
100  ‎$0‎MAPA20200022947‎$a‎Villa-Murillo, Adriana
24510‎$a‎Forest-genetic method to optimize parameter design of multiresponse experiment‎$c‎Adriana Villa-Murillo, Andrés Carrión, Antonio Sozzi
520  ‎$a‎We propose a methodology for the improvement of the parameter design that consists of the combination of Random Forest (RF) with Genetic Algorithms (GA) in 3 phases: normalization, modelling and optimization. The first phase corresponds to the previous preparation of the data set by using normalization functions. In the second phase, we designed a modelling scheme adjusted to multiple quality characteristics and we have called it Multivariate Random Forest (MRF) for the determination of the objective function. Finally, in the third phase, we obtained the optimal combination of parameter levels with the integration of properties of our modeling scheme and desirability functions in the establishment of the corresponding GA. Two illustrative cases allow us to compare and validate the virtues of our methodology versus other proposals involving Artificial Neural Networks (ANN) and Simulated Annealing (SA).
650 4‎$0‎MAPA20080611200‎$a‎Inteligencia artificial
650 4‎$0‎MAPA20080553128‎$a‎Algoritmos
650 4‎$0‎MAPA20080624842‎$a‎Redes neuronales artificiales
650 4‎$0‎MAPA20080547424‎$a‎Genética
650 4‎$0‎MAPA20080604721‎$a‎Análisis multivariante
7001 ‎$0‎MAPA20200022985‎$a‎Carrión, Andrés
7001 ‎$0‎MAPA20200022992‎$a‎Sozzi, Antonio
7730 ‎$w‎MAP20200034445‎$t‎Revista Iberoamericana de Inteligencia Artificial‎$d‎IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-‎$x‎1988-3064‎$g‎31/12/2020 Volumen 23 Número 66 - diciembre 2020 , p. 9-25
856  ‎$q‎application/pdf‎$w‎1108789‎$y‎Recurso electrónico / Electronic resource