Nowa wersja platformy, zawierająca wyłącznie zasoby pełnotekstowe, jest już dostępna.
Przejdź na https://bibliotekanauki.pl

PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2010 | Vol. 19, No. 4 | 451-462
Tytuł artykułu

A Double-Circle Algorithm for Ore Classification

Autorzy
Wybrane pełne teksty z tego czasopisma
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper proposes a double-circle algorithm to classify ore stockpiles according to their particle size distribution. The algorithm is particularly suitable for yard automation systems in large iron and steel works, since its result can be used directly as a reliable basis for stackers and reclaimers controller. The paper explains the concept as well as related method, which consists of four steps to detect ore granularity and classes. A series of experiments in industrial environments proved that this novel algorithm improves the reliability of ore classifiers, compared with the classic ones.
Wydawca

Rocznik
Strony
451-462
Opis fizyczny
Bibliogr. 13 poz., il., tab.
Twórcy
autor
autor
  • Shanghai Jiao Tong University, School of EE, Shanghai 200240, China
Bibliografia
  • [1] Bhattacharyya, A. On a measure of divergence between two statistical populations denned by their probability distributions, Bulletin of the Calcutta Mathematical Society, 35: 99-109, 1943
  • [2] Serra J. Image analysis and mathematical morphology. London: Academic Press, 1982
  • [3] J. Canny. A Computational Approach to Edge Detection, IEEE Trans. on Pattern Analysis and Machine Intelligence, 8(6): 679-698, 1986
  • [4] A. Aggarwal, L. J. Guibas, J. Saxe, and P. W. Shor. A linear-time algorithm for computing the Voronoi diagram of a convex polygon, Discrete Comput. Geom., 4(6):591-604, 1989
  • [5] J Mao, AK Jain. Texture classification and segmentation using multiresolution simultaneous au-toregressive models, Pattern Recognition, 25(2): 173-188, 1992
  • [6] Kohavi, Ron. A study of cross-validation and bootstrap for accuracy estimation and model selection. Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 2 (12): 1137-1143, 1995
  • [7] Adrian Ford, Alan Roberts. Color Space Conversions, 1998
  • [8] C. F. Moraa, A. K. H. Kwana, H. C. Chana. Particle size distribution analysis of coarse aggregate using digital image processing, Cement and Concrete Research, 28(6): 921-932, 1998
  • [9] A. Jillavenkatesa, S. J. Dapkunas, Lin-Sien Lum. Particle Size Characterization, NIST Special Publication. 960-1, 2001
  • [10] David Meyer, Friedrich Leisch, Kurt Hornik. The support vector machine under test. Neurocomputing, 55(1-2): 169-186, 2003
  • [11] WANG Lixin. A Course in Fuzzy Systems & Control, United States: Pearson Education, 2003
  • [12] Linda G. Shapiro, George C. Stockman. Computer Vision. New Jersey, United States: Addison Wesley, 2005
  • [13] Dean, S., Illowsky, B. Descriptive Statistics: Histogram. Retrieved from the Connexions Web site: http://cnx.Org/content/ml6298/l.ll/ ; 2009.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-article-BWAD-0024-0033
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.