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    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/125529
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/125529

    Title: 單層學習神經網路配合多輸出節點應用於期貨預測
    The Single-hidden Layer Feedforward Neural Networks with Multiple Output Nodes for Futures Forecast
    Authors: 鄭玉婕
    Jheng, Yu-Jie
    Contributors: 蔡瑞煌
    Tsaih, Rua-Huan
    Jheng, Yu-Jie
    Keywords: 人工神經網絡
    強記、 軟化與整合
    Artificial Neural Network
    Cramming and Softening and Integrating
    Hybrid Artificial Intelligence
    Futures Forecast
    Decision Support System
    Date: 2019
    Issue Date: 2019-09-05 15:44:43 (UTC+8)
    Abstract:   蔡,許和賴(1998)提出了一種混合人工智能(AI)方法,該方法集成了基於規則的系統和人工神經網絡(ANN)技術,用以預測標準普爾500指數期貨未來價格變化的方向。他們聲稱混合方法可以促進更可靠的智能係統的開發,以模擬專家思維和支持決策過程。
      Tsaih, Hsu and Lai (1998) proposed a hybrid artificial intelligence (AI) method that integrates rule-based system techniques and artificial neural network (ANN) techniques to predict the direction of future S&P 500 index futures price changes. They claim that hybrid approaches can facilitate the development of more reliable intelligent systems to simulate expert thinking and support decision-making processes.
      This study differs from Tsaih, Hsu & Lai (1998) in two ways. First, the study has two additional state variables for the research purpose. Secondly, we use the single hidden layer feedforward neural network (SLFN) and the Cramming, Softening and Integrating (CSI) learning algorithm instead of the Reasoning Neural Networks (RN) and the Back Propagation learning algorithm.
      The empirical results show that the proposed decision support system with CSI learning algorithm is effective in predicting Non-obvious and Unobserved data during the 7-year test period from 2007 to 2013. The decision support system provides advice to the user when making decisions.
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    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0106356019
    Data Type: thesis
    DOI: 10.6814/NCCU201900839
    Appears in Collections:[資訊管理學系] 學位論文

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