• DocumentCode
    3409049
  • Title

    Developing model of grey clustering based on grey number

  • Author

    Junjuan, Liu ; Aizeng, Li ; FenYi, Dong

  • Author_Institution
    Sch. of Inf. & Manage. Sci., Henan Agric. Univ., Zhengzhou, China
  • fYear
    2009
  • fDate
    10-12 Nov. 2009
  • Firstpage
    708
  • Lastpage
    712
  • Abstract
    Analysis result shows that many things are grey system. According to the classical grey theory, the grey number was adopted to express the evaluation indices and clustering thresholds. Furthermore, grey number formula was presented and clustering model was built based on the trapezoid whitening weight function. The possibility idea of comparing interval number was introduced into grey number compare. Three signalized intersections were given to prove the effectiveness and reasonableness of the presented model, evaluation results conform to the actual analysis, the maximum clustering value [0.416, 0.839] of the intersection A1 belong to the III type, the maximum clustering value [0.202, 0.728] and [0.413, 0.645] of the intersection A2 and A3 belong to the IV type, and the second maximum clustering value of the intersection A2 belong to V type, the second maximum clustering value of the intersection A3 belong to the III type, not only it can carry on clustering according to the maximum value, but also act accurate sequencing in accordance with the second largest value.
  • Keywords
    grey systems; pattern clustering; clustering model; grey clustering; grey number; grey system; grey theory; interval number; trapezoid whitening weight function; Agricultural engineering; Appraisal; Clustering algorithms; Decision making; Filtration; Information management; Intelligent systems; Investments; Traffic control; Turning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Grey Systems and Intelligent Services, 2009. GSIS 2009. IEEE International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4914-9
  • Electronic_ISBN
    978-1-4244-4916-3
  • Type

    conf

  • DOI
    10.1109/GSIS.2009.5408221
  • Filename
    5408221