• DocumentCode
    3114851
  • Title

    Application of Combined Grey Neural Network and Data Mining in Information Technology Education

  • Author

    Qu Zhiming ; Hou Wei

  • Author_Institution
    Sch. of Civil Eng., Hebei Univ. of Eng., Handan, China
  • fYear
    2009
  • fDate
    13-14 Dec. 2009
  • Firstpage
    163
  • Lastpage
    166
  • Abstract
    Using the theory of grey system, data mining technology and radial basis function (RBF) neural network method, a new model, the combined model of grey system and RBF neural network, is setup, which aims at solving the user´s received data safety analysis. The results show that, in short-term prediction of data safety, GM is an effective way and RBF has perfect ability to study and map. The combined model of grey system and neural network, to a large extent, has the dual properties of trend and fluctuation under the condition of combining with the time-dependent sequence data. It is concluded that great improvement comparing with any method of trend prediction and simple factor in combined model of grey system and neural network comparing with the any model of grey system and RBF neural network in data safety analysis.
  • Keywords
    data mining; grey systems; information science education; radial basis function networks; RBF neural network; combined grey neural network; data mining technology; data safety analysis; grey system theory; information technology education; radial basis function neural network; time-dependent sequence data; Data analysis; Data engineering; Data mining; Delta modulation; Educational technology; Information technology; Neural networks; Predictive models; Safety; Systems engineering education; data mining; data safety analysis; grey system; radial basic functions neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Training, 2009. ETT '09. Second International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-0-7695-3936-2
  • Electronic_ISBN
    978-1-4244-5527-0
  • Type

    conf

  • DOI
    10.1109/ETT.2009.8
  • Filename
    5381414