An evaluation model of artificial neural network to predict stable width in gravel bed rivers

International Journal of Environmental Science and Technology

Volumn 9, Issue 2, 2012, Pages 333-342

  Tahershamsi, A ^a   Majdzade Tabatabai, M R ^b   Shirkhani, R ^a  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

^b SHAHID BEHESHTI UNIVERSITY   (Iran)

Author keywords

Gravel bed rivers; Regime width; River morphology; Total load sediment

Indexed keywords

ALLUVIAL CHANNELS; ALLUVIAL RIVER; BANKFULL DISCHARGE; CHANNEL DESIGN; CHANNEL FORMATION; COMPLEX PROBLEMS; DATA SETS; EVALUATION MODELS; GRAVEL-BED CHANNEL; GRAVEL-BED RIVERS; HIDDEN LAYERS; HIDDEN NEURONS; INDEPENDENT PARAMETERS; INPUT DATAS; INTELLIGENT MODELS; MULTI-LAYER PERCEPTRON NETWORKS; NON-DIMENSIONAL EQUATIONS; OPTIMUM NETWORKS; PHYSICAL PROCESS; REGIME WIDTH; REGRESSION EQUATION; RIVER MORPHOLOGY; TOTAL LOAD;

DISCHARGE (FLUID MECHANICS); ESTIMATION; FORECASTING; GRAVEL; MORPHOLOGY; REGRESSION ANALYSIS; RIVERS;

NEURAL NETWORKS;

EID: 84859955758     PISSN: 17351472     EISSN: 17352630     Source Type: Journal    
DOI: 10.1007/s13762-012-0036-8     Document Type: Article

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