SCOPUS 정보 검색 플랫폼

Volumn 71, Issue 5-6, 2010, Pages 431-437

Prediction of electrophoretic mobilities of organic acids using artificial neural networks with three different training functions

(2) Garkani Nejad, Zahra a Seyedbagheri, Seyed Ali b

a VALI E ASR UNIVERSITY OF RAFSANJAN (Iran)

b PAYAME NOOR UNIVERSITY (Iran)

Author keywords

Artificial neural network; Chemometrics; Electrophoretic mobility; Multiple linear regression; Organic acid; Quantitative structure mobility relationship

Indexed keywords

CARBOXYLIC ACID;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; CHEMOMETRIC ANALYSIS; CONTROLLED STUDY; CORRELATION COEFFICIENT; ELECTROPHORETIC MOBILITY; INTERMETHOD COMPARISON; IONIZATION; MATHEMATICAL MODEL; MOLECULAR SIZE; MULTIPLE LINEAR REGRESSION ANALYSIS; NONLINEAR SYSTEM; PREDICTION; PREDICTOR VARIABLE; PRIORITY JOURNAL; PROCESS DEVELOPMENT; PROCESS OPTIMIZATION; QUANTITATIVE STRUCTURE ACTIVITY RELATION; VALIDATION PROCESS;

EID: 77952092726 PISSN: 00095893 EISSN: 16121112 Source Type: Journal
DOI: 10.1365/s10337-009-1466-4 Document Type: Article

Times cited : (5)

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