کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10559110 | 969218 | 2005 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Classification of Antarctic algae by applying Kohonen neural network with 14 elements determined by inductively coupled plasma optical emission spectrometry
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Optical emission spectrometers can generate results, which sometimes are not easy to interpret, mainly when the analyses involve classifications. To make simultaneous data interpretation possible, the Kohonen neural network is used to classify different Antarctic algae according to their taxonomic groups from the determination of 14 analytes. The Kohonen neural network architecture used was 5Ã5 neurons, thus reducing 14-dimension input data to two-dimensional space. The input data were 14 analytes (As, Co, Cu, Fe, Mn, Sr, Zn, Cd, Cr, Mo, Ni, Pb, Se, V) with their concentrations, determined by inductively coupled plasma optical emission spectrometry in 11 different species of algae. Three taxonomic groups (Rhodophyta, Phaeophyta and Cholorophyta) can be differentiated and classified through only their Cu content.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Spectrochimica Acta Part B: Atomic Spectroscopy - Volume 60, Issue 5, 30 June 2005, Pages 725-730
Journal: Spectrochimica Acta Part B: Atomic Spectroscopy - Volume 60, Issue 5, 30 June 2005, Pages 725-730
نویسندگان
L. Balbinot, P. Smichowski, S. Farias, M.A.Z. Arruda, C. Vodopivez, R.J. Poppi,