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Title page for etd-0118107-221940


URN etd-0118107-221940 Statistics This thesis had been viewed 3644 times. Download 2836 times.
Author Wei-Li Shen
Author's Email Address No Public.
Department Information Management
Year 2006 Semester 1
Degree Master Type of Document Master's Thesis
Language zh-TW.Big5 Chinese Page Count 73
Title Prediction of Time-Series Data by Integration of Regression Trees and Artificial Neural Network
For Example, Taiwan Stock Index Future and Gross National Product
Keyword
  • Artificial Neural
  • Regression Trees
  • Data Mining
  • Data Mining
  • Regression Trees
  • Artificial Neural
  • Abstract The related researches showed Artificial Neural Network technology have higher forecast accuracy of Prediction, the premise is use suitable parameters to network model, Because of the appropriate parameters design can have better prediction accuracy compared to the statistical method thought adopting more than data indication for analysis is more easily to find the relevant parameter. On contrariety, it will involve the unnecessarily interference and conduction in the prediction accuracy reduction.
    This research method combines Regression Trees with Artificial Neural Network technology to Taiwan Stock Index Future prediction, using the Liner Regression and Regression Trees as filters to find the indexes that affect the FIFX. Then adapting to Neural Network Model as input. The experiential results shows the MSE of our method is only 0.13 which is better than the previous research 0.15.
    Advisor Committee
  • Prof. Yen-Ju Yang - advisor
  • Shih-Sheng Chen - co-chair
  • Yu-cheng Kao - co-chair
  • Files indicate access worldwide
    Date of Defense 2007-01-12 Date of Submission 2007-02-09


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