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Volumn 381, Issue 3, 2005, Pages 788-794
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Evaluation of a generalized regression artificial neural network for extending cadmium's working calibration range in graphite furnace atomic absorption spectrometry
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Author keywords
Artificial neural networks; Cadmium; Calibration curve; Graphite furnace atomic absorption spectrometry (GFAAS); Modeling
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Indexed keywords
ABSORPTION SPECTROSCOPY;
BACKPROPAGATION;
CADMIUM;
CALIBRATION;
COMPUTER SIMULATION;
CONCENTRATION (PROCESS);
FURNACES;
GRAPHITE;
MATHEMATICAL MODELS;
POLYNOMIALS;
REGRESSION ANALYSIS;
BACKPROPAGATION ARTIFICIAL NEURAL NETWORKS (BPANN);
GENERALIZED REGRESSION ARTIFICIAL NEURAL NETWORKS (GRANN);
NONLINEAR CALIBRATION;
ONE-PASS PROCESS;
NEURAL NETWORKS;
CADMIUM;
DRINKING WATER;
GRAPHITE;
ACCURACY;
ANALYTIC METHOD;
ANALYTICAL ERROR;
ARTICLE;
ARTIFICIAL NEURAL NETWORK;
ATOMIC ABSORPTION SPECTROMETRY;
CALCULATION;
CALIBRATION;
COMPUTER PROGRAM;
DILUTION;
EVALUATION;
FREQUENCY ANALYSIS;
FURNACE;
INTERMETHOD COMPARISON;
MATHEMATICAL MODEL;
NONLINEAR SYSTEM;
NORMAL DISTRIBUTION;
PREDICTION;
QUALITY CONTROL;
REGRESSION ANALYSIS;
RISK ASSESSMENT;
STATISTICAL ANALYSIS;
WATER CONTAMINATION;
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EID: 15044353499
PISSN: 16182642
EISSN: None
Source Type: Journal
DOI: 10.1007/s00216-004-2918-1 Document Type: Article |
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Times cited : (6)
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References (22)
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