We deal with the determination of the composition of bronze alloys measured through Laser-Induced Breakdown Spectroscopy (LIBS) analysis. The relation between LIBS spectra and bronze alloy composition, represented by means of the concentrations of constituting elements, is modeled by adopting an ensemble of learning machines, fed with different inputs. Then, the combiner computes the final response. The results obtained on the test set show that the ensemble model manages to determine the composition of alloy samples with mean squared error of about 6.53 10^-2.
An ensemble of learning machines for quantitative analysis of bronze alloys
D'ANDREA, ELEONORA;LAZZERINI, BEATRICE
2016-01-01
Abstract
We deal with the determination of the composition of bronze alloys measured through Laser-Induced Breakdown Spectroscopy (LIBS) analysis. The relation between LIBS spectra and bronze alloy composition, represented by means of the concentrations of constituting elements, is modeled by adopting an ensemble of learning machines, fed with different inputs. Then, the combiner computes the final response. The results obtained on the test set show that the ensemble model manages to determine the composition of alloy samples with mean squared error of about 6.53 10^-2.File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
IECON_D'Andrea_Lazzerini.pdf
accesso aperto
Descrizione: Articolo principale
Tipologia:
Documento in Pre-print
Licenza:
Tutti i diritti riservati (All rights reserved)
Dimensione
390.36 kB
Formato
Adobe PDF
|
390.36 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
