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    Discussion of “Performance of Neural Networks in Daily Streamflow Forecasting” by S. Birikundavyi, R. Labib, H. T. Trung, and J. Rousselle 

    Source: Journal of Hydrologic Engineering:;2004:;Volume ( 009 ):;issue: 006
    Author(s): Hikmet Kerem Cigizoglu
    Publisher: American Society of Civil Engineers
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    Application of Generalized Regression Neural Networks to Intermittent Flow Forecasting and Estimation 

    Source: Journal of Hydrologic Engineering:;2005:;Volume ( 010 ):;issue: 004
    Author(s): Hikmet Kerem Cigizoglu
    Publisher: American Society of Civil Engineers
    Abstract: The majority of artificial neural network (ANN) applications to water resources data employ the feed-forward back-propagation (FFBP) method. This study used an ANN algorithm, the generalized regression neural network (GRNN), ...
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    Application of Gamma Autoregressive Model to Analysis of Dry Periods 

    Source: Journal of Hydrologic Engineering:;1998:;Volume ( 003 ):;issue: 003
    Author(s): Hikmet Kerem Cigizoglu; M. Bayazit
    Publisher: American Society of Civil Engineers
    Abstract: In water resources projects the determination of the dry period characteristics of rivers is important especially in arid and semiarid regions. Classical run and range analyses are based mainly on the use of the first-order ...
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    Application of Gamma Autoregressive Model to Analysis of Dry Periods 

    Source: Journal of Hydrologic Engineering:;2000:;Volume ( 005 ):;issue: 001
    Author(s): K. Srinivasan; V. V. Srinivas; Hikmet Kerem Cıgˇızogˇlu
    Publisher: American Society of Civil Engineers
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