Artificial neural networks (ANNs) are non-linear computational tools suitable to a great host of practical application due to their flexibility and adaptability. However, their application to the resolution of chemometric problems is relatively recent (early 1990s). In this communication, different artificial neural networks architectures are presented and their application to different kinds of chemomettic problems (mainly classification and regression) is discussed by means of examples taken from the authors' experience, stressing the pros and cons of ANNs with respect to traditional chemometric techniques. (c) 2007 Elsevier B.V. All rights reserved.
Artificial neural networks in chemometrics: History, examples and perspectives / Marini, Federico; Bucci, Remo; Magri', Antonio; Magri', Andrea. - In: MICROCHEMICAL JOURNAL. - ISSN 0026-265X. - STAMPA. - 88:2(2008), pp. 178-185. (Intervento presentato al convegno 1st International Symposium on Multivariate Analysis and Chemometrics for Cultural Heritage and Environment tenutosi a Nemi, ITALY nel OCT 02-04, 2006) [10.1016/j.microc.2007.11.008].
Artificial neural networks in chemometrics: History, examples and perspectives
MARINI, Federico;BUCCI, Remo;MAGRI', Antonio;MAGRI', Andrea
2008
Abstract
Artificial neural networks (ANNs) are non-linear computational tools suitable to a great host of practical application due to their flexibility and adaptability. However, their application to the resolution of chemometric problems is relatively recent (early 1990s). In this communication, different artificial neural networks architectures are presented and their application to different kinds of chemomettic problems (mainly classification and regression) is discussed by means of examples taken from the authors' experience, stressing the pros and cons of ANNs with respect to traditional chemometric techniques. (c) 2007 Elsevier B.V. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
