期刊
TALANTA
卷 124, 期 -, 页码 123-138出版社
ELSEVIER
DOI: 10.1016/j.talanta.2014.01.034
关键词
Experimental design; Response transformation; Multiple response optimization; Desirability function
资金
- Universidad Nacional del Litoral (Projects CAI+D 2011) [11-11, 11-25, 11-14]
- CONICET (Consejo Nacional de Investigaciones Cientificas y Tecnicas Project PIP-2012 [455]
- ANPCyT (Agencia Nacional de Promocion Cientifica y Tecnologica, Project PICT) [2011-0005]
A review about the application of response surface methodology (RSM) when several responses have to be simultaneously optimized in the field of analytical methods development is presented. Several critical issues like response transformation, multiple response optimization and modeling with least squares and artificial neural networks are discussed. Most recent analytical applications are presented in the context of analytLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquimica y Ciencias Biologicas, Universidad Nacional del Litoral, CC. 242, S3000ZAA Santa Fe, ArgentinaLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquimica y Ciencias Biologicas, Universidad Nacional del Litoral, CC. 242, S3000ZAA Santa Fe, Argentinaical methods development, especially in multiple response optimization procedures using the desirability function. (C) 2014 Elsevier BM. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据