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    政大典藏 > College of Commerce > Department of MIS > Theses >  Item 140.119/87031


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/87031


    Title: 整合式智慧型系統在資訊篩選上之研究--結合類神經網路與模糊理論以證券市場預測為例
    The research on development of an integrated intelligent system for information filtering:using artificial neural network and fuzzy theory on stock market forecasting
    Authors: 楊豐松
    Yang, Feng-Sueng
    Contributors: 林我聰
    Lin, Woo-Tsong
    楊豐松
    Yang, Feng-Sueng
    Keywords: 資訊篩選
    類神經網路
    模糊理論
    整合式系統
    智慧型系統
    Information Filter
    Artificial Neural Network
    Fuzzy Theory
    System Intergration
    Date: 1997
    Issue Date: 2016-04-28 09:42:50 (UTC+8)
    Abstract: 在資訊爆炸的時代，處於日趨複雜的環境及多重資訊來源管道之下，如何從大量及瑣碎的資訊中找出「重要且有用」的部份，藉以輔助企業或個人制定正確的決策，並降低資訊取得的成本，是資訊人員在設計資訊系統時所必須考量的重要因素之一，因此，資訊篩選(Information filtering)已成為當務之急，更顯示出其重要性。
    At the time of information explosion, how to filter the important and useful parts from a large and trivial information pool is one of the most important factors considering in designing information systems which are used to assist users making right decisions by MIS managers. The purpose of this research is to integrate two technologies. Artificial Neural Network and Fuzzy Theory, to develop a generalized algorithm to filter important information. We hope that using this algorithm we can (1)filter the important decision variables, (2)decrease the information usage, and (3)reduce the cost of information collection. Finally, we made four experiments on the XOR system and stock market forecasting to test the accuracy and practicability of the information filter algorithm. The results of experiments showed that the algorithm could filter the important information correctly and quickly.
    Description: 碩士
    國立政治大學
    資訊管理學系
    Source URI: http://thesis.lib.nccu.edu.tw/record/#B2002002497
    Data Type: thesis
    Appears in Collections:[Department of MIS] Theses

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