A comparison of eight metamodeling techniques for the simulation of N 2O fluxes and N leaching from corn crops

Environmental Modelling and Software

Volumn 34, Issue , 2012, Pages 51-66

  Villa Vialaneix, Nathalie ^a,b   Follador, Marco ^c   Ratto, Marco ^c   Leip, Adrian ^c  

^a UNIVERSITÉ DE PERPIGNAN   (France)

^b UNIVERSITÉ DE TOULOUSE   (France)

^c JOINT RESEARCH CENTRE   (Italy)

Author keywords

Agriculture; Metamodeling; N leaching; N 2O flux; Neural network; Random forest; Splines; SVM

Indexed keywords

ARABLE LAND; BAGGING METHOD; CONTINENTAL SCALE; CROPPING SYSTEMS; DATA SETS; DETAILED MODELING; ENVIRONMENTAL COSTS; ESTIMATION PERFORMANCE; FARMING ACTIVITIES; KRIGING; META MODEL; META-MODELING TECHNIQUE; METAMODELING; MODELING FRAMEWORKS; MULTI LAYER PERCEPTRON; NONLINEAR INTERACTIONS; NONPARAMETRIC APPROACHES; RANDOM FORESTS; SIMULATION SPEED; SIMULATION-BASED METHOD; SVM; TRAINING DATASET;

AGRICULTURE; DECISION TREES; FORESTRY; NEURAL NETWORKS; SPLINES;

LEACHING;

AGRICULTURAL LAND; ARTIFICIAL NEURAL NETWORK; COST-BENEFIT ANALYSIS; DATA SET; FLUX MEASUREMENT; INTEGRATED APPROACH; KRIGING; LEACHING; MAIZE; NITROGEN; NITROGEN CYCLE; NITROUS OXIDE; NONLINEARITY; NUMERICAL MODEL; OXYGEN;

AGRICULTURE; CORN; LAND USE; LEACHING; MATHEMATICAL MODELS; NEURAL NETWORKS; NITROGEN OXIDES; SIMULATION; STATISTICAL ANALYSIS;

EUROPE;

ZEA MAYS;

EID: 84859103898     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2011.05.003     Document Type: Article

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