Artificial neural network approach for prediction of ammonia emission from field-applied manure and relative significance assessment of ammonia emission factors

European Journal of Agronomy

Volumn 26, Issue 4, 2007, Pages 425-434

  Lim, Youngil ^a   Moon, Young Sil ^a   Kim, Tae Wan ^b  

^a Department of Chemical Engineering   (South Korea)

^b Faculty of Plant Life and Environmental Sciences   (South Korea)

Author keywords

Ammonia emission; Artificial neural network (ANN); Livestock manure; Michaelis Menten equation; Multivariate linear regression (MLR); Principle component analysis (PCA); Weight partitioning method (WPM)

Indexed keywords

AMMONIA; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; ESTIMATION METHOD; MANURE; NONLINEARITY; PRINCIPAL COMPONENT ANALYSIS; SLURRY; SOIL EMISSION;

EID: 33947661902     PISSN: 11610301     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eja.2007.01.008     Document Type: Article

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