Development of ann-based models to predict biogas and methane productions in anaerobic treatment of molasses wastewater

International Journal of Green Energy

Volumn 10, Issue 9, 2013, Pages 885-907

  Yetilmezsoy, Kaan ^a   Turkdogan, F Ilter ^a   Temizel, Ilknur ^a   Gunay, Asli ^a  

^a YILDIZ TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Artificial neural networks; Biogas; Methane; Modeling; Molasses wastewater; Up flow anaerobic sludge blanket

Indexed keywords

ARTIFICIAL NEURAL NETWORK MODELS; DETERMINATION COEFFICIENTS; MINIMUM MEAN SQUARED ERROR; MOLASSES WASTEWATER; SCALED CONJUGATE GRADIENT ALGORITHM; UP-FLOW ANAEROBIC SLUDGE BLANKET REACTORS; UPFLOW ANAEROBIC SLUDGE BLANKETS; VOLUMETRIC ORGANIC LOADING;

ALKALINITY; BACKPROPAGATION ALGORITHMS; CHEMICAL OXYGEN DEMAND; CONJUGATE GRADIENT METHOD; FORECASTING; MEAN SQUARE ERROR; METHANE; MODELS; NEURAL NETWORKS; OPTIMIZATION; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; TRANSFER FUNCTIONS; VOLATILE FATTY ACIDS; WASTEWATER TREATMENT;

BIOGAS;

ANOXIC CONDITIONS; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; BIOGAS; METHANE; NUMERICAL MODEL; PRINCIPAL COMPONENT ANALYSIS; WASTE TREATMENT; WASTEWATER;

EID: 84879203931     PISSN: 15435075     EISSN: 15435083     Source Type: Journal    
DOI: 10.1080/15435075.2012.727116     Document Type: Article

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