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    篇名/題名:Deterministic fuzzy time series model for forecasting enrollments
    摘要:The fuzzy time series has recently received increasing attention because of its capability of dealing with vague and incomplete
    data. There have been a variety of models developed to either improve forecasting accuracy or reduce computation overhead.
    However, the issues of controlling uncertainty in forecasting, effectively partitioning intervals, and consistently achieving
    forecasting accuracy with different interval lengths have been rarely investigated. This paper proposes a novel deterministic
    forecasting model to manage these crucial issues. In addition, an important parameter, the maximum length of subsequence in a
    fuzzy time series resulting in a certain state, is deterministically quantified. Experimental results using the University of Alabama's
    enrollment data demonstrate that the proposed forecasting model outperforms the existing models in terms of accuracy, robustness,
    and reliability. Moreover, the forecasting model adheres to the consistency principle that a shorter interval length leads to more
    accurate results.
    類型:期刊論文
    西元出版年:2007
    著作語言:zh-TW
    作者:Cheng, Yi Chung
    學校系所:國際企業經營系碩士班