Artificial neural networks for computer-aided modelling and optimisation in micellar electrokinetic chromatography

被引：37
|
作者：
Havel, J
Breadmore, M
Macka, M
Haddad, PR
机构：
[1] Univ Tasmania, Sch Chem, Hobart, Tas 7001, Australia
[2] Masaryk Univ, Fac Sci, Dept Analyt Chem, Brno 61137, Czech Republic
来源：
JOURNAL OF CHROMATOGRAPHY A | 1999年 / 850卷 / 1-2期
关键词：
neural networks; artificial; optimisation; computer modelling; experimental design; metal complexes;
D O I：
10.1016/S0021-9673(99)00634-2
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
The separation process in capillary micellar electrochromatography (MEKC) can be modelled using artificial neural networks (ANNs) and optimisation of MEKC methods can be facilitated by combining ANNs with experimental design. ANNs have shown attractive possibilities for non-linear modelling of response surfaces in MEKC and it was demonstrated that by combining ANN modelling with experimental design, the number of experiments necessary to search and find optimal separation conditions can be reduced significantly. A neu; general approach for computer-aided optimisation in MEKC has been proposed which, because of its general validity, can also be applied in other separation techniques. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：345 / 353
页数：9
相关论文
共 50 条
  • [1] Computer-aided learning in artificial neural networks
    Ringwood, JV
    Galvin, G
    IEEE TRANSACTIONS ON EDUCATION, 2002, 45 (04) : 380 - 387
  • [2] Predicting and evaluating separation quality of micellar electrokinetic capillary chromatography by artificial neural networks
    Liu, BF
    Zhang, JF
    Lu, YT
    ELECTROPHORESIS, 2002, 23 (09) : 1279 - 1284
  • [3] Artificial neural networks modeling for computer-aided design of microwave filter
    Ciminski, AS
    MIKON-2002: XIV INTERNATIONAL CONFERENCE ON MICROWAVES, RADAR AND WIRELESS COMMUNICATIONS, VOLS 1-3, PROCEEDINGS, 2002, : 96 - 99
  • [4] Artificial Neural Networks for Microwave Computer-Aided Design: The State of the Art
    Feng, Feng
    Na, Weicong
    Jin, Jing
    Zhang, Jianan
    Zhang, Wei
    Zhang, Qi-Jun
    IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2022, 70 (11) : 4597 - 4619
  • [5] Mixed-integer optimisation of graph neural networks for computer-aided molecular design
    Mcdonald, Tom
    Tsay, Calvin
    Schweidtmann, Artur M.
    Yorke-Smith, Neil
    COMPUTERS & CHEMICAL ENGINEERING, 2024, 185
  • [6] Impact of missing data in training artificial neural networks for computer-aided diagnosis
    Markey, MK
    Patel, A
    PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA'04), 2004, : 351 - 354
  • [7] Artificial Neural Networks in Computer-Aided Drug Design: An Overview of Recent Advances
    Cheirdaris, Dionysios G.
    GENEDIS 2018: COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2020, 1194 : 115 - 125
  • [8] Optimization of resolution in micellar electrokinetic chromatography via computer-aided variation of concentrations of sodium dodecyl sulfate and acetonitrile as modifier
    Butehorn, U
    Pyell, U
    JOURNAL OF CHROMATOGRAPHY A, 1997, 772 (1-2) : 27 - 38
  • [9] COMPUTER-AIDED ANALYSIS AND DERIVATION FOR ARTIFICIAL NEURAL SYSTEMS
    WANG, DM
    SCHURMANN, B
    IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 1992, 18 (08) : 728 - 735
  • [10] A review of artificial neural networks applications in microwave computer-aided design (invited article)
    Burrascano, P
    Fiori, S
    Mongiardo, M
    INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, 1999, 9 (03) : 158 - 174
12345