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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/77281


    Title: Forecasting in fuzzy systems
    Authors: Wang, Hsiao-fan;Tsaur, Ruey-chyn
    Contributors: 淡江大學管理科學學系
    Keywords: Fuzzy linear regression;forecasting;extrapolation;independent variable;dependent variable
    Date: 2011-03
    Issue Date: 2012-06-14 10:31:38 (UTC+8)
    Publisher: Singapore: World Scientific Publishing Co. Pte. Ltd.
    Abstract: Fuzzy regression has been applied to marketing, management, and sales forecasting for many years. In this paper, two types of forecasting methods within the framework of fuzzy regression analysis are discussed. The first type is a conventional forecasting method, which intends to find the value of a dependent variable when the given values of independent variables are beyond the range covered by historical data. The second type considers forecasting in which the necessary values of independent variables are desired when the given value of a dependent variable does not fall within the range of historical data. While the first type can be applied in planning, the second one is useful for control and management. Numerical examples are provided for illustration.
    Relation: International Journal of Information Technology & Decision Making 10(2), pp.333-352
    DOI: 10.1142/S021962201100435X
    Appears in Collections:[管理科學學系暨研究所] 期刊論文

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