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2010 | 8 | 6 | 1298-1304
Tytuł artykułu

Herbal drug raw materials differentiation by neural networks using non-metals content

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Three-layer artificial neural networks (ANN) capable of recognizing the type of raw material (herbs, leaves, flowers, fruits, roots or barks) using the non-metals (N, P, S, Cl, I, B) contents as inputs were designed. Two different types of feed-forward ANNs - multilayer perceptron (MLP) and radial basis function (RBF), best suited for solving classification problems, were used. Phosphorus, nitrogen, sulfur and boron were significant in recognition; chlorine and iodine did not contribute much to differentiation. A high recognition rate was observed for barks, fruits and herbs, while discrimination of herbs from leaves was less effective. MLP was more effective than RBF.
Wydawca

Czasopismo
Rocznik
Tom
8
Numer
6
Strony
1298-1304
Opis fizyczny
Daty
wydano
2010-12-01
online
2010-10-08
Twórcy
  • Department of Analytical Chemistry, Medical University of Gdansk, 80-416, Gdansk, Poland
  • Department of Analytical Chemistry, Medical University of Gdansk, 80-416, Gdansk, Poland, marwes@gumed.edu.pl
Bibliografia
  • [1] H.B. Matthews, G.W. Lucier, K.D. Fisher, Environmental Health Perspectives 107, 773 (1999) http://dx.doi.org/10.2307/3454572[Crossref]
  • [2] P.R.G.M. De Smet, K. Keller, R. Hansel, R.F. Chandler, Adverse Effects of Herbal Drugs (Springer-Verlag, Heidelberg, 1997) vol. 1–3
  • [3] W.M. Bandaranayake, In: I. Ahmad, F. Aqil, M. Owais (Eds.), Modern Phytomedicine. Turning Medicinal Plants into Drugs (Wiley-VCH, Weinheim, 2006) 25
  • [4] M.Y. Lovkova, G.N. Buzuk, S.M. Sokolova, N.I. Kliment’eva, Applied Biochemistry and Microbiology 37, 229 (2001) http://dx.doi.org/10.1023/A:1010254131166[Crossref]
  • [5] C. Bishop, Neural networks for pattern recognition (Oxford University Press, Oxford 1995)
  • [6] S. Haykin, Neural networks: A Comprehensive foundation, 2nd edition (Prentice Hall, New Jersey, 1999)
  • [7] Statistica Neural Networks (manual) (Statsoft Inc, Tulsa OK, 2007)
  • [8] M. Wesolowski, P. Konieczynski, Chemia Analityczna (Warsaw) 41, 377 (1996)
  • [9] M. Wesolowski, P. Konieczynski, B. Ulewicz, Journal of Thermal Analysis and Calorimetry 60, 299 (2000) http://dx.doi.org/10.1023/A:1010142517579[Crossref]
  • [10] M. Wesolowski, P. Konieczynski, V. Medrzycka, Chemia Analityczna (Warsaw) 46, 697 (2001)
  • [11] M. Wesolowski, P. Konieczynski, Thermochimica Acta 397, 171 (2003) http://dx.doi.org/10.1016/S0040-6031(02)00319-2[Crossref]
  • [12] M. Wesolowski, P. Konieczynski, International Journal of Pharmaceutics 262, 29 (2003) http://dx.doi.org/10.1016/S0378-5173(03)00317-X[Crossref]
  • [13] M. Wesolowski, B. Suchacz, Fresenius Journal of Analytical Chemistry 371, 323 (2001) http://dx.doi.org/10.1007/s002160100921[Crossref]
  • [14] J. Zupan, J. Gastaiger, Neural networks in chemistry and drug design (Wiley, New York, 1999)
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.-psjd-doi-10_2478_s11532-010-0105-0
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