Statsoft Electronic Statistics Textbook
Statsoft Electronic Statistics Textbook 2016
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. Q 2005 Elsevier B.V. All rights reserved. Free program descargar crack para internet manager gratis. The purpose of this research is to develop Machine Learning techniques for quantitative analysis of illicit narcotics from mixtures based on their Raman spectra, with the aim of improving on traditional chemometric quantification techniques. In this paper, we investigate the use of wavelet transforms for data and noise reduction, in conjunction with neural networks designed using genetic algorithms, for the prediction of cocaine concentration in mixtures using their Raman spectral data.