• DocumentCode
    2486190
  • Title

    Data mining-based engineering project grading technique

  • Author

    Chang, Chunguang ; Song, Xiaoyu ; Gao, Bo ; Kong, Fanwen

  • Author_Institution
    Sch. of Manage., Shenyang Jianzhu Univ., Shenyang
  • fYear
    2008
  • fDate
    25-27 June 2008
  • Firstpage
    3542
  • Lastpage
    3546
  • Abstract
    The purpose of this paper is to improve the quality of engineering project grading, the basic processes of data mining technique are introduced. Taking the engineering project grading as background, the implement cycles such as business understanding, data understanding, data preparation, modeling, evaluation and deployment are studied in detail. During modeling, the decision tree is adopted as analyzing modeling, and the conventional C4.5 algorithm is adapted. The adapted algorithm is applied to the engineering project grading, and its result is compared with that of conventional C4.5 algorithm. The comparing result demonstrates that for the complex system such as engineering project grading, it can improve in a certain extent on precision and obtained structure of decision tree, it can improve the quality of engineering project grading.
  • Keywords
    business data processing; data mining; decision trees; engineering computing; C4.5 algorithm; data mining; engineering project grading; Data engineering; Data mining; Decision trees; Delta modulation; Engineering management; Intelligent control; Manufacturing automation; Manufacturing processes; Project management; Pulp manufacturing; C4.5 algorithm; Data mining; Decision tree; Engineering project; Grading;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-2113-8
  • Electronic_ISBN
    978-1-4244-2114-5
  • Type

    conf

  • DOI
    10.1109/WCICA.2008.4593487
  • Filename
    4593487