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    Wavelet-Based Hydrological Time Series Forecasting

    Source: Journal of Hydrologic Engineering:;2016:;Volume ( 021 ):;issue: 005
    Author:
    Yan-Fang Sang
    ,
    Vijay P. Singh
    ,
    Fubao Sun
    ,
    Yaning Chen
    ,
    Yong Liu
    ,
    Moyuan Yang
    DOI: 10.1061/(ASCE)HE.1943-5584.0001347
    Publisher: American Society of Civil Engineers
    Abstract: These days wavelet analysis is becoming popular for hydrological time series simulation and forecasting. There are, however, a set of key issues influencing the wavelet-aided data preprocessing and modeling practice that need further discussion. This article discusses four key issues related to wavelet analysis: discrepant use of continuous and discrete wavelet methods, choice of mother wavelet, choice of temporal scale, and uncertainty evaluation in wavelet-aided forecasting. The article concludes with a personal reflection on solving the four issues for improving and supplementing relevant wavelet studies, especially wavelet-based artificial intelligence modeling.
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      Wavelet-Based Hydrological Time Series Forecasting

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    contributor authorYan-Fang Sang
    contributor authorVijay P. Singh
    contributor authorFubao Sun
    contributor authorYaning Chen
    contributor authorYong Liu
    contributor authorMoyuan Yang
    date accessioned2017-05-08T22:34:04Z
    date available2017-05-08T22:34:04Z
    date copyrightMay 2016
    date issued2016
    identifier other49837667.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/82776
    description abstractThese days wavelet analysis is becoming popular for hydrological time series simulation and forecasting. There are, however, a set of key issues influencing the wavelet-aided data preprocessing and modeling practice that need further discussion. This article discusses four key issues related to wavelet analysis: discrepant use of continuous and discrete wavelet methods, choice of mother wavelet, choice of temporal scale, and uncertainty evaluation in wavelet-aided forecasting. The article concludes with a personal reflection on solving the four issues for improving and supplementing relevant wavelet studies, especially wavelet-based artificial intelligence modeling.
    publisherAmerican Society of Civil Engineers
    titleWavelet-Based Hydrological Time Series Forecasting
    typeJournal Paper
    journal volume21
    journal issue5
    journal titleJournal of Hydrologic Engineering
    identifier doi10.1061/(ASCE)HE.1943-5584.0001347
    treeJournal of Hydrologic Engineering:;2016:;Volume ( 021 ):;issue: 005
    contenttypeFulltext
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