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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/17322

    Title: 非線性RCA模式應用於水文時序之研究
    Other Titles: Studies on nonlinear RCA model with application on hydrological time series
    Authors: 虞國興;林河山
    Contributors: 淡江大學水資源及環境工程學系
    Keywords: 隨機係數自迴歸模式;水文時序;參數推估;預測能力;Random Coefficient Autoregressive Model;Hydrological Time Series;Parameter Estimation;Forecasting Ability
    Date: 1997-12-17
    Issue Date: 2009-08-04 14:43:29 (UTC+8)
    Abstract: 本研究主要探討非線性時間序列模式中之隨機係數自迴歸模式,簡稱RCA模式, 及其應用於台灣河川月流量資料之適用性, 並與傳統線性自迴歸模式, 做一比較。 本研究於合成資料參數推估時RCA模式受推估法及樣本數之影響較大; 於實測資料分析上, 就統計特性保存能力方面, RCA模式於平均值及變異數之保存能力則優於AR模式, 另於預測能力表現上, 於台灣南部地區, 除勢後RCA模式則皆具較除勢後之AR模式為佳。 總體而言, 除勢後RCA模式於預測能力與統計特性保存能力上之表現均優於除勢後AR模式。
    The major objective of this present study is to investigate the nonlinear time series model that is Random Coefficient Autoregressive Model, denoted RCA model in brief. The linear autoregressive model is also compared with nonlinear models. In this research, the parameters estimation of the nonlinear model are studied. The monthly riverflow data in Taiwan are employed to investigate the aptness of these nonlinear time series models. The results indicate that the estimation of parameter for RCA model is affected by sample size and estimation method. The RCA model has better forecasting ability than AR model when the data are detrended in south area of Taiwan. In conclusion, the nonlinear time series models are appropriate for riverflow in Taiwan.
    Relation: 八十六年度農業工程研討會論文集,頁 113-119
    Appears in Collections:[Graduate Institute & Department of Water Resources and Environmental Engineering] Proceeding

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