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Artificial neural network techniques for analysis of ion backscattering spectra

หน่วยงาน Central Queensland University, Australia

รายละเอียด

ชื่อเรื่อง : Artificial neural network techniques for analysis of ion backscattering spectra
นักวิจัย : Li, Michael M. , Fan, Xiaolong. , Verma, Brijesh. , Balsys, Ronald J. , O'Connor, D. J. (D. John), 1952-
คำค้น : Artificial intelligence. , 671401 Scientific instrumentation , 280212 Neural Networks, Genetic Alogrithms and Fuzzy Logic , TBA. , 861503 Scientific Instruments. , 8615 Instrumentation. , 86 Manufacturing. , 080108 Neural, Evolutionary and Fuzzy Computation. , 0801 Artificial Intelligence and Image Processing. , 08 Information and Computing Sciences. , Neural networks (Computer science) , Scientific apparatus and instruments. , Neural networks -- Resilient backpropagation -- Spectral analysis -- Intelligence techniques
หน่วยงาน : Central Queensland University, Australia
ผู้ร่วมงาน : -
ปีพิมพ์ : 2548
อ้างอิง : http://hdl.cqu.edu.au/10018/24700 , cqu:3877
ที่มา : Li, M, Fan, X, Verma, B, Balsys, R, & O'Connor, D J 2005, 'Artificial neural network techniques for analysis of ion backscattering spectra', paper presented at 2005 International Conference on Artificial Intelligence, Las Vegas.
ความเชี่ยวชาญ : -
ความสัมพันธ์ : Proceedings of the International Conference on Artificial Intelligence, IC-AI '05, June 27-30, 2005, Las Vegas, Nevada, U.S.A. / Hamid R. Arabnia, Rose Joshua (eds.). Las Vegas. : CSREA Press, 2005. p. 1-7 7 pages Refereed 1932415661 , ACQUIRE [electronic resource] : Central Queensland University Institutional Repository.
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

Ion backscattering spectrometry is an analysis technology that is dedicated to the compositional analysis of samples with the thickness of μm level. The problem of spectral data analysis, which is to determine the sample structure from the measured spectra, is generally ill-posed. In this study, artificial neural network (ANN) techniques have been developed for spectral data analysis. A multilayer feedforward neural network was constructed and applied to the specific case of SiGe thin films on a silicon substrate. The network was trained by the resilient backpropagation algorithm with hundreds of simulated spectra of samples for which the structures are known. Then the trained network was applied to analyse spectra with unknown structure of samples. The ANN prediction results are excellent. The constructed neural network can handle properly redundancies, which were caused by the constraint of output variables.

บรรณานุกรม :
Li, Michael M. , Fan, Xiaolong. , Verma, Brijesh. , Balsys, Ronald J. , O'Connor, D. J. (D. John), 1952- . (2548). Artificial neural network techniques for analysis of ion backscattering spectra.
    กรุงเทพมหานคร : Central Queensland University, Australia.
Li, Michael M. , Fan, Xiaolong. , Verma, Brijesh. , Balsys, Ronald J. , O'Connor, D. J. (D. John), 1952- . 2548. "Artificial neural network techniques for analysis of ion backscattering spectra".
    กรุงเทพมหานคร : Central Queensland University, Australia.
Li, Michael M. , Fan, Xiaolong. , Verma, Brijesh. , Balsys, Ronald J. , O'Connor, D. J. (D. John), 1952- . "Artificial neural network techniques for analysis of ion backscattering spectra."
    กรุงเทพมหานคร : Central Queensland University, Australia, 2548. Print.
Li, Michael M. , Fan, Xiaolong. , Verma, Brijesh. , Balsys, Ronald J. , O'Connor, D. J. (D. John), 1952- . Artificial neural network techniques for analysis of ion backscattering spectra. กรุงเทพมหานคร : Central Queensland University, Australia; 2548.