• DocumentCode
    569403
  • Title

    Wheat Cultivar Classifications Based on Tabu Search and Fuzzy C-means Clustering Algorithm

  • Author

    Li Lin ; Liu Suhua

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China
  • fYear
    2012
  • fDate
    17-19 Aug. 2012
  • Firstpage
    493
  • Lastpage
    496
  • Abstract
    Aimed at the characteristic of recognizing wheat seed, a method is proposed based on fuzzy theory. In this paper, Fuzzy C-means Clustering is introduced and remarked firstly. On the basis of systematic analysis of current algorithms, Tabu search is inducted into fuzzy clustering to solve the locality and the sensitivity of the initial condition of Fuzzy C-means Clustering. Then, this paper proposes the fuzzy discern method based on approach degree and the principle of closest. The deficiency of dose-approximation value is proposed. Finally, it provides the design method and the new algorithm. Simulation results show that this method has good performance regarding both the quality of obtained answer and efficiency.
  • Keywords
    approximation theory; crops; fuzzy set theory; pattern clustering; sensitivity; approach degree; dose-approximation value; fuzzy C-means clustering algorithm; fuzzy discern method; fuzzy theory; initial condition locality; initial condition sensitivity; tabu search; wheat cultivar classifications; wheat seed recognition; Algorithm design and analysis; Character recognition; Clustering algorithms; Genetic algorithms; Optimization; Search problems; Approach degree; Fuzzy C-means Clustering; Fuzzy Pattern Recognition; Tabu Search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4673-2406-9
  • Type

    conf

  • DOI
    10.1109/ICCIS.2012.365
  • Filename
    6300551