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Qualitative identification of tea categories by near infrared spectroscopy and support vector machine
Journal of Pharmaceutical and Biomedical Analysis, Volume 41, Issue 4, 16 June 2006, Pages 1198-1204
Jiewen Zhao, Quansheng Chen, Xingyi Huang and C.H. Fang
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Discrimination of varieties of tea using near infrared spectroscopy by principal component analysis and BP model
Journal of Food Engineering, In Press, Corrected Proof, Available online 11 May 2006,
Yong He, Xiaoli Li and Xunfei Deng
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Generalisation Performance of Artificial Neural Networks for Near Infrared Spectral Analysis
Biosystems Engineering, Volume 94, Issue 1, May 2006, Pages 7-18
W. Wang and J. Paliwal
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Spectral analysis and fingerprinting for biomedia characterisation
Journal of Biotechnology, Volume 113, Issues 1-3, 30 September 2004, Pages 211-230
Marie-Noëlle Pons, Sébastien Le Bonté and Olivier Potier
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Linear and non-linear pattern recognition models for classification of fruit from visible–near infrared spectra
Chemometrics and Intelligent Laboratory Systems, Volume 51, Issue 2, 24 July 2000, Pages 201-216
Jaesoo Kim, Alistair Mowat, Philip Poole and Nikola Kasabov
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The optimal brain surgeon for pruning neural network architecture applied to multivariate calibration
Analytica Chimica Acta, Volume 375, Issues 1-2, 27 November 1998, Pages 187-195
R. J. Poppi and D. L. Massart
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Non-linear modelling of chemical data by combinations of linear and neural net methods
Analytica Chimica Acta, Volume 283, Issue 1, 15 November 1993, Pages 508-517
Beata Walczak and Wolfhard Wegscheider
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Gasoline quality prediction using gas chromatography and FTIR spectroscopy: An artificial intelligence approach
Fuel, Volume 85, Issue 4, March 2006, Pages 553-558
K. Brudzewski, A. Kesik, K. Kołodziejczyk, U. Zborowska and J. Ulaczyk
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Classification of premium and regular gasoline by gas chromatography/mass spectrometry, principal component analysis and artificial neural networks
Forensic Science International, Volume 132, Issue 1, 12 March 2003, Pages 26-39
Philip Doble, Mark Sandercock, Eric Du Pasquier, Peter Petocz, Claude Roux and Michael Dawson
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Neural network approach to qualitative identification of fuels and oils from laser induced fluorescence spectra
Analytica Chimica Acta, Volume 285, Issues 1-2, 20 January 1994, Pages 237-246
John M. AndrewsStephen H. Lieberman
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Applicability of high-absorbance MIR spectroscopy in industrial quality control of reformed gasolines
Chemometrics and Intelligent Laboratory Systems, Volume 46, Issue 1, 15 February 1999, Pages 41-55
José M. Andrade, María S. Sánchez and Luis A. Sarabia
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Characterization of crude petroleum by NIR
Journal of Petroleum Science and Engineering, Volume 51, Issues 1-2, 16 April 2006, Pages 127-137
F.S. Falla, C. Larini, G.A.C. Le Roux, F.H. Quina, L.F.L. Moro and C.A.O. Nascimento
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Performance and exhaust emissions of a gasoline engine using artificial neural network
Applied Thermal Engineering, In Press, Corrected Proof, Available online 7 July 2006,
Cenk Sayin, H. Metin Ertunc, Murat Hosoz, Ibrahim Kilicaslan and Mustafa Canakci
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Modeling and optimization for the secondary reaction of FCC gasoline based on the fuzzy neural network and genetic algorithm
Chemical Engineering and Processing, In Press, Corrected Proof, Available online 2 June 2006,
Zhiwen Wang, Bolun Yang, Chun Chen, Jun Yuan and Longyan Wang
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Octane number prediction for gasoline blends
Fuel Processing Technology, Volume 87, Issue 6, June 2006, Pages 505-509
Nikos Pasadakis, Vassilis Gaganis and Charalambos Foteinopoulos
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Classification of gasoline with supplement of bio-products by means of an electronic nose and SVM neural network
Sensors and Actuators B: Chemical, Volume 113, Issue 1, 17 January 2006, Pages 135-141
K. Brudzewski, S. Osowski, T. Markiewicz and J. Ulaczyk
Thanks a lot!
