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Titolo:
GENETIC PROGRAMMING - A NOVEL METHOD FOR THE QUANTITATIVE-ANALYSIS OFPYROLYSIS MASS-SPECTRAL DATA
Autore:
GILBERT RJ; GOODACRE R; WOODWARD AM; KELL DB;
Indirizzi:
UNIV COLL WALES ABERYSTWYTH,DEPT BIOL SCI ABERYSTWYTH SY23 3DA DYFED WALES UNIV COLL WALES ABERYSTWYTH,DEPT BIOL SCI ABERYSTWYTH SY23 3DA DYFED WALES
Titolo Testata:
Analytical chemistry
fascicolo: 21, volume: 69, anno: 1997,
pagine: 4381 - 4389
SICI:
0003-2700(1997)69:21<4381:GP-ANM>2.0.ZU;2-Z
Fonte:
ISI
Lingua:
ENG
Soggetto:
ARTIFICIAL NEURAL NETWORKS; MULTIVARIATE CALIBRATION; SPECTROMETRY; OVERPRODUCTION; ALGORITHMS; BROTHS;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Citazioni:
38
Recensione:
Indirizzi per estratti:
Citazione:
R.J. Gilbert et al., "GENETIC PROGRAMMING - A NOVEL METHOD FOR THE QUANTITATIVE-ANALYSIS OFPYROLYSIS MASS-SPECTRAL DATA", Analytical chemistry, 69(21), 1997, pp. 4381-4389

Abstract

A technique for the analysis of multivariate data by genetic programming (GP) is described, with particular reference to the quantitative analysis of orange juice adulteration data collected by pyrolysis mass spectrometry (PyMS). The dimensionality of the input space was reducedby ranking variables according to product moment correlation or mutual information with the outputs. The GP technique as described gives predictive errors equivalent to, if not better than, more widespread methods such as partial least squares and artificial neural networks but additionally can provide a means for easing the interpretation of the correlation between input and output variables. The described application demonstrates that by using the GP method for analyzing PyMS data the adulteration of orange juice with 10% sucrose solution can be quantified reliably over a 0-20% range with an RMS error in the estimate ofsimilar to 1%.

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Documento generato il 02/04/20 alle ore 09:29:07