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Wyświetlanie 1-2 z 2
Tytuł:
Multicriterial Analysis of Explosives in the THz Range
Autorzy:
Ryniec, R.
Piszczek, M.
Szustakowski, M.
Powiązania:
https://bibliotekanauki.pl/articles/1506835.pdf
Data publikacji:
2010-12
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
42.81.Bm
42.81.Cn
42.81.Dp
Opis:
The increasing interest in the development of identification methods of explosives in THz region over the past few years has been observed because of potential terrorist threats. To determine specific spectra properties of materials both possible spectroscopic methods - time domain spectroscopy and Fourier transform infrared spectroscopy are used to analyze different classes of compounds. This paper deals with an identification problem of more than one compound. This task was solved mathematically by means of the following methods: Monte Carlo including principal components analysis methods and analytic methods. Investigations were limited to a detector, which based on a single-frequency quantum dot matrix in 0.3 ÷ 1.3 THz range. The mathematical analysis also includes the atmosphere influence on propagation of THz waves. By means of the presented methods we indicated fourteen optimal frequency points and next we managed to identify one explosive from a set of ten explosives.
Źródło:
Acta Physica Polonica A; 2010, 118, 6; 1235-1238
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Terahertz Frequency Domain Spectroscopy Identification System Based on Decision Trees
Autorzy:
Ryniec, R.
Zagrajek, P.
Pałka, N.
Powiązania:
https://bibliotekanauki.pl/articles/1418036.pdf
Data publikacji:
2012-11
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
42.81.Bm
42.81.Cn
42.81.Dp
Opis:
The application of pattern recognition methodology within chemistry, biology and other science domains, especially in security systems is becoming more and more important. Many classification algorithms are available in literature but decision trees are the most commonly exploited because of their ease of implementation and understanding in comparison to other classification algorithms. Decision trees are powerful and popular tools for classification and prediction. In contrast to neural networks, decision trees represent rules, which can readily be expressed so that humans can understand them or even directly use in a database. In this paper we present an algorithm of construction of decision trees and a classification rule extraction based on a logical relationship between attributes and a generalized decision function. Moreover, correctness and efficiency of the algorithm was experimentally validated in a terahertz system, where spectra of explosives were measured in reflection configuration.
Źródło:
Acta Physica Polonica A; 2012, 122, 5; 891-895
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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