Supersaturated experimental designs:: new approaches to building and using it Part II.: Solving supersaturated designs by genetic algorithms

被引：18
|
作者：
Cela, R [1 ]
Martínez, E [1 ]
Carro, AM [1 ]
机构：
[1] Univ Santiago de Compostela, Fac Quim, Dept Quim Analit Nutr & Bromatol, E-15706 Santiago De Compostela, Spain
来源：
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 2001年 / 57卷 / 02期
关键词：
genetic algorithm; all-subsets regression; matrices;
D O I：
10.1016/S0169-7439(01)00127-7
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new procedure for the resolution of supersaturated matrices is presented. This procedure is based on genetic algorithm-driven regression, using an efficient system of genetic operators' competence. Genetic regression is compared with stepwise regression and all-subsets regression that has been proposed to solve this type of matrices, presented results show that this new genetic-driven procedure outperforms both stepwise and all-subsets regression procedures. The proposed method shows satisfactory efficiency and robustness for data even in the presence of gross accidental errors. All studies were conducted by a dedicated toolkit that is briefly described. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：75 / 92
页数：18
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