Increasing the working calibration range by means of artificial neural networks for the determination of cadmium by graphite furnace atomic absorption spectrometry

Talanta

Volumn 63, Issue 2, 2004, Pages 425-431

  Hernández Caraballo, Edwin A ^a   Avila Gómez, Rita M ^a,c   Rivas, Francklin ^b   Burguera, Marcela ^a   Burguera, José L ^a  

^a FACULTAD DE CIENCIAS   (Venezuela)

^b UNIVERSIDAD DE LOS ANDES   (Venezuela)

^c Depto de Procesos Agroindustriales   (Venezuela)

Author keywords

Artificial neural networks (ANNs); Backpropagation; Cadmium; Calibration curves; Graphite furnace atomic absorption spectrometry (GFAAS)

Indexed keywords

ABSORPTION SPECTROSCOPY; CURVE FITTING; GRAPHITE; NEURAL NETWORKS; POTABLE WATER; STANDARDS; TRANSFER FUNCTIONS;

GRAPHITE FURNACE ATOMIC ABSORPTION SPECTROMETRY (GFAAS); NEURONS;

CADMIUM METALLURGY;

CADMIUM; DRINKING WATER;

ACCURACY; ANALYTIC METHOD; ARTICLE; ARTIFICIAL NEURAL NETWORK; ATOMIC ABSORPTION SPECTROMETRY; CALIBRATION; CHEMICAL PROCEDURES; CHEMICAL REACTION; DILUTION; FURNACE; MOLECULAR MODEL; NERVE CELL; STATISTICAL SIGNIFICANCE; WATER SAMPLING; WORK CAPACITY;

EID: 2142645810     PISSN: 00399140     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.talanta.2003.11.013     Document Type: Article

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