An improved genetic programming technique for the classification of Raman spectra

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@Article{journals/kbs/HennessyMCR05,

• title = "An improved genetic programming technique for the classification of Raman spectra",
• author = "Kenneth Hennessy and Michael G. Madden and Jennifer Conroy and Alan G. Ryder",
• journal = "Knowledge Based Systems",
• year = "2005",
• number = "4-5",
• volume = "18",
• pages = "217--224",
• month = aug,
• note = "AI-2004, Cambridge, England, 13th-15th December 2004",
• bibdate = "2005-11-24",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/journals/kbs/kbs18.html#HennessyMCR05",
• keywords = "genetic algorithms, genetic programming, Machine learning, Neural networks, Spectroscopy, Raman",
• DOI = "doi:10.1016/j.knosys.2004.10.001",
• abstract = "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.",

}

Genetic Programming entries for Kenneth Hennessy Michael G Madden Jennifer Conroy Alan G Ryder

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