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    Hydrometeorological Parameters in Prediction of Soil Temperature by Means of Artificial Neural Network: Case Study in Wyoming 

    Source: Journal of Hydrologic Engineering:;2013:;Volume ( 018 ):;issue: 006
    Author(s): Mohammad Zounemat-Kermani
    Publisher: American Society of Civil Engineers
    Abstract: The current study was undertaken to analyze the performance of three back-propagation training algorithms of artificial neural network (ANN) along with a multiple linear regression model (MLR) for transient simulation of ...
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    Modeling of Dissolved Oxygen Applying Stepwise Regression and a Template-Based Fuzzy Logic System 

    Source: Journal of Environmental Engineering:;2014:;Volume ( 140 ):;issue: 001
    Author(s): Mohammad Zounemat-Kermani; Miklas Scholz
    Publisher: American Society of Civil Engineers
    Abstract: This paper develops a template-based fuzzy inference system (TFIS) capable of simulating the dissolved oxygen (DO) concentration of an example stream by using daily data (2009–2012). Stepwise regression (SR) analysis and ...
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    Closure to “Assessment of Artificial Intelligence–Based Models and Metaheuristic Algorithms in Modeling Evaporation” by Mohammad Zounemat-Kermani, Ozgur Kisi, Jamshid Piri, and Amin Mahdavi-Meymand 

    Source: Journal of Hydrologic Engineering:;2020:;Volume ( 025 ):;issue: 009:;page 07020015-1
    Author(s): Mohammad Zounemat-Kermani; Ozgur Kisi; Jamshid Piri; Amin Mahdavi-Meymand
    Publisher: ASCE
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    River Suspended Sediment Load Prediction: Application of ANN and Wavelet Conjunction Model 

    Source: Journal of Hydrologic Engineering:;2011:;Volume ( 016 ):;issue: 008
    Author(s): Taher Rajaee; Vahid Nourani; Mohammad Zounemat-Kermani; Ozgur Kisi
    Publisher: American Society of Civil Engineers
    Abstract: Accurate suspended sediment prediction is an integral component of sustainable water resources and environmental systems. This study considered artificial neural network (ANN), wavelet analysis and ANN combination (WANN), ...
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    Prediction of Critical Velocity in Pipeline Flow of Slurries Using TLBO Algorithm: A Comprehensive Study 

    Source: Journal of Pipeline Systems Engineering and Practice:;2020:;Volume ( 011 ):;issue: 002
    Author(s): Sareh Sayari; Amin Mahdavi-Meymand; Mohammad Zounemat-Kermani
    Publisher: ASCE
    Abstract: Proper estimation of the critical flow velocity of slurries (Vc) is one of the most important parameters to design slurry transport in pipeline systems. In this study, three standard soft computing data-driven models ...
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    Assessment of Artificial Intelligence–Based Models and Metaheuristic Algorithms in Modeling Evaporation 

    Source: Journal of Hydrologic Engineering:;2019:;Volume ( 024 ):;issue: 010
    Author(s): Mohammad Zounemat-Kermani; Ozgur Kisi; Jamshid Piri; Amin Mahdavi-Meymand
    Publisher: American Society of Civil Engineers
    Abstract: Evaporation (Ep) has a vital importance for the management and development of water resources projects. In this study two scenarios are considered in prediction of monthly pan evaporation. The first scenario challenges the ...
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