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    Artificial Models for Interbasin Flow Prediction in Southern Turkey 

    Source: Journal of Hydrologic Engineering:;2009:;Volume ( 014 ):;issue: 007
    Author(s): M. Erol Keskin; Dilek Taylan
    Publisher: American Society of Civil Engineers
    Abstract: The aim of this study was to develop an optimum flow prediction method, based on the adaptive neural-based fuzzy inference system (ANFIS) and artificial neural network (ANN). Each methodology was applied to river flow ...
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    Closure to “Artificial Models for Interbasin Flow Prediction in Southern Turkey” by M. Erol Keskin and Dilek Taylan 

    Source: Journal of Hydrologic Engineering:;2010:;Volume ( 015 ):;issue: 009
    Author(s): M. Erol Keskin; Dilek Taylan
    Publisher: American Society of Civil Engineers
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    Estimating Evaporation Using ANFIS 

    Source: Journal of Irrigation and Drainage Engineering:;2006:;Volume ( 132 ):;issue: 005
    Author(s): Özlem Terzi; M. Erol Keskin; E. Dilek Taylan
    Publisher: American Society of Civil Engineers
    Abstract: Water resources engineering assessment requires simple but effective evaporation estimation procedures, especially from readily measurable meteorological factors. Unfortunately, such approaches are rather scarce in the ...
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    Predicting Hydrological Droughts of Long-Narrow Type Drainage Basin Using Monte Carlo Technique 

    Source: Journal of Hydrologic Engineering:;2024:;Volume ( 029 ):;issue: 003:;page 04024013-1
    Author(s): Tahsin Baykal; Emine Dilek Taylan; Ekinhan Eriskin; Özlem Terzi
    Publisher: American Society of Civil Engineers
    Abstract: Drought forecasting is a critical aspect of water resource management, where droughts have substantial economic and environmental impacts. This study employs a Monte Carlo–based approach, complemented by statistical ...
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