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    Adaptive Neurofuzzy Computing Technique for Evapotranspiration Estimation 

    Source: Journal of Irrigation and Drainage Engineering:;2007:;Volume ( 133 ):;issue: 004
    Author(s): Özgür Kişi; Özgür Öztürk
    Publisher: American Society of Civil Engineers
    Abstract: The accuracy of an adaptive neurofuzzy computing technique in estimation of reference evapotranspiration
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    Discussion of “Prediction of Daily Dewpoint Temperature Using a Model Combining the Support Vector Machine with Firefly Algorithm” by Eiman Tamah Al-Shammari, Kasra Mohammadi, Afram Keivani, Siti Hafizah Ab Hamid, Shatirah Akib, Shahaboddin Shamshirband, 

    Source: Journal of Irrigation and Drainage Engineering:;2017:;Volume ( 143 ):;issue: 011
    Author(s): Ozgur Kisi
    Publisher: American Society of Civil Engineers
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    Discussion of “Monthly Mean Streamflow Prediction Based on Bat Algorithm-Support Vector Machine” by Bing Xing, Rong Gan, Guodong Liu, Zhongfang Liu, Jing Zhang, and Yufeng Ren 

    Source: Journal of Hydrologic Engineering:;2016:;Volume ( 021 ):;issue: 008
    Author(s): Ozgur Kisi
    Publisher: American Society of Civil Engineers
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    Discussion of “Estimation of Furrow Irrigation Sediment Loss Using an Artificial Neural Network” by Bradley A. King, David L. Bjorneberg, Thomas J. Trout, Luciano Mateos, Danielle F. Araujo, and Raimundo N. Costa 

    Source: Journal of Irrigation and Drainage Engineering:;2017:;Volume ( 143 ):;issue: 005
    Author(s): Ozgur Kisi
    Publisher: American Society of Civil Engineers
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    Workload Distribution Framework for the Parallel Solution of Large Structural Models on Heterogeneous PC Clusters 

    Source: Journal of Computing in Civil Engineering:;2010:;Volume ( 024 ):;issue: 002
    Author(s): Ozgur Kurc
    Publisher: American Society of Civil Engineers
    Abstract: One of the main problems of substructure-based parallel solution methods is the imbalances in the condensation times of substructures when direct solvers are used. Such imbalances usually decrease the performance of the ...
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    Discussion of “Evapotranspiration Modeling Using Second-Order Neural Networks” by Sirisha Adamala, N. S. Raghuwanshi, Ashok Mishra, and Mukesh K. Tiwari 

    Source: Journal of Hydrologic Engineering:;2015:;Volume ( 020 ):;issue: 009
    Author(s): Özgür Kişi
    Publisher: American Society of Civil Engineers
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    River Flow Modeling Using Artificial Neural Networks 

    Source: Journal of Hydrologic Engineering:;2004:;Volume ( 009 ):;issue: 001
    Author(s): Özgür Kişi
    Publisher: American Society of Civil Engineers
    Abstract: This paper demonstrates the application of artificial neural networks (ANNs) in predicting mean monthly streamflow. The estimation of flow is very important for reservoir operation policy; therefore, in this study, based ...
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    Streamflow Forecasting Using Different Artificial Neural Network Algorithms 

    Source: Journal of Hydrologic Engineering:;2007:;Volume ( 012 ):;issue: 005
    Author(s): Özgür Kişi
    Publisher: American Society of Civil Engineers
    Abstract: Forecasts of future events are required in many activities associated with planning and operation of the components of a water resources system. For the hydrologic component, there is a need for both short term and long ...
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    Discussion of “Daily Pan Evaporation Modeling in a Hot and Dry Climate” by J. Piri, S. Amin, A. Moghaddamnia, A. Keshavarz, D. Han, and R. Remesan 

    Source: Journal of Hydrologic Engineering:;2010:;Volume ( 015 ):;issue: 008
    Author(s): Ozgur Kisi
    Publisher: American Society of Civil Engineers
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    Discussion of “Comparative Study of ANNs versus Parametric Methods in Rainfall Frequency Analysis” by Jianxun He and Caterina Valeo 

    Source: Journal of Hydrologic Engineering:;2010:;Volume ( 015 ):;issue: 004
    Author(s): Ozgur Kisi
    Publisher: American Society of Civil Engineers
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