Selection of the Robust Streamflow Forecasting Model Using Wavelet-Entropy Complexity Criterion

سال انتشار: 1394
محل انتشار: دهمین کنگره بین المللی مهندسی عمران
کد COI اختصاصی: ICCE10_0792
زبان مقاله: انگلیسی
تعداد مشاهده: 823

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نویسندگان

Vahid Nourani

Professor, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran

Faranak Tootoonchi

M.Sc. Student, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran

Sevil Ranjbar

چکیده

As one of the most important hydrological processes, Runoff modeling is highly dominant in accurate study of a watershed. Many models are yet being developed in order to define such a complex process, therefore using a measure to scope relative complexity of a watershed results in choosing more appropriate model related to its characteristics. In this study, the runoff process of five different watersheds, which are different in land use, population growth and complexity, are modeled. In order to consider relative complexities, Wavelet-Entropy measure is introduced as a new complexity measurement tool. It is deduced that only in areas with higher complexity levels, Complex modeling structures are needed (such as ANN and WANN) and in those with respective lower wavelet-entropy measure, auto-regressive models (such as ARIMA and ARIMAX) can be consumed efficiently, therefore using complex models are not necessary

کلیدواژه ها

Black box Modeling, Rainfall- Runoff Modeling, Wavelet Transform, Artificial Neural Network, Wavelet-Entropy Complexity Measure

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