An improved genetic programming technique for the classification of Raman spectra

被引：15

作者：

Hennessy, K ^{[1
]}

Madden, MG

Conroy, J

Ryder, AG

机构：

[1] Natl Univ Ireland Univ Coll Galway, Dept Informat Technol, Galway, Ireland

[2] Natl Univ Ireland Univ Coll Galway, Dept Chem, Galway, Ireland

来源：

KNOWLEDGE-BASED SYSTEMS | 2005年 / 18卷 / 4-5期

关键词：

machine learning; genetic programming; neural networks; spectroscopy; Raman;

D O I：

10.1016/j.knosys.2004.10.001

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The aim of this study is to evaluate the effectiveness of genetic programming relative to that of more commonly-used methods for the identification of components within mixtures of materials using Raman spectroscopy. A key contribution of the genetic programming technique proposed in this research is that it explicitly aims to optimise the certainty levels associated with discovered rules, so as to minimize the chance of misclassification of future samples. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：217 / 224

页数：8

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