Modeling of ammonia emission in the USA and EU countries using an artificial neural network approach

Protocol for developing ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling

(2014) Wenyan Wu et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Ammonia emissions in the United States, European Union, and China derived by high-resolution inversion of ammonium wet deposition data: Interpretation with a new agricultural emissions inventory (MASAGE_NH3)

(2014) F. Paulot et al.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

A new method for estimating greenhouse gases and ammonia emissions from livestock buildings

(2013) José Barrancos et al.   ATMOSPHERIC ENVIRONMENT

Air quality prediction using optimal neural networks with stochastic variables

(2013) Ana Russo et al.   ATMOSPHERIC ENVIRONMENT

Forecasting of Greenhouse Gas Emissions in Serbia Using Artificial Neural Networks

(2013) D. Radojević et al.   Energy Sources Part A-Recovery Utilization and Environmental Effects

Ammonia in the atmosphere: a review on emission sources, atmospheric chemistry and deposition on terrestrial bodies

(2013) Sailesh N. Behera et al.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH

Forecasting GHG emissions using an optimized artificial neural network model based on correlation and principal component analysis

(2013) Davor Z. Antanasijević et al.   International Journal of Greenhouse Gas Control

Ammonia Emission Model for Whole Farm Evaluation of Dairy Production Systems

(2013) C. Alan Rotz et al.   JOURNAL OF ENVIRONMENTAL QUALITY

Intentional versus unintentional nitrogen use in the United States: trends, efficiency and implications

(2012) Benjamin Z. Houlton et al.   BIOGEOCHEMISTRY

Ozone prediction on the basis of neural networks, support vector regression and methods with uncertainty

(2012) Petr Hájek et al.   Ecological Informatics

Manure-DNDC: a biogeochemical process model for quantifying greenhouse gas and ammonia emissions from livestock manure systems

(2012) Changsheng Li et al.   NUTRIENT CYCLING IN AGROECOSYSTEMS

PM10 emission forecasting using artificial neural networks and genetic algorithm input variable optimization

(2012) Davor Z. Antanasijević et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Cost-effective control of air quality and greenhouse gases in Europe: Modeling and policy applications

(2011) Markus Amann et al.   ENVIRONMENTAL MODELLING & SOFTWARE

A refined index of model performance

(2011) Cort J. Willmott et al.   INTERNATIONAL JOURNAL OF CLIMATOLOGY

Comparison of ANN and principal component analysis-multivariate linear regression models for predicting the river flow based on developed discrepancy ratio statistic

(2010) Roohollah Noori et al.   EXPERT SYSTEMS WITH APPLICATIONS

Power transformer differential protection using neural network Principal Component Analysis and Radial Basis Function Neural Network

(2010) Manoj Tripathy   SIMULATION MODELLING PRACTICE AND THEORY

Fault Classification in Phase-Locked Loops Using Back Propagation Neural Networks

(2009) Jayabalan Ramesh et al.   ETRI JOURNAL

Bottom-up uncertainty estimates of global ammonia emissions from global agricultural production systems

(2008) A.H.W. Beusen et al.   ATMOSPHERIC ENVIRONMENT

Application of different training methodologies for the development of a back propagation artificial neural network retention model in ion chromatography

(2008) Tomislav Bolanča et al.   JOURNAL OF CHEMOMETRICS

An Earth-system perspective of the global nitrogen cycle

(2008) Nicolas Gruber et al.   NATURE

How a century of ammonia synthesis changed the world

(2008) Jan Willem Erisman et al.   Nature Geoscience

Prediction of hourly air pollutant concentrations near urban arterials using artificial neural network approach

(2008) Ming Cai et al.   TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT

Selection and validation of parameters in multiple linear and principal component regressions

(2007) J.C.M. Pires et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Combining principal component regression and artificial neural networks for more accurate predictions of ground-level ozone

(2007) S ALALAWI et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Modeling and prediction of ventilation methane emissions of U.S. longwall mines using supervised artificial neural networks

(2007) C. Özgen Karacan   INTERNATIONAL JOURNAL OF COAL GEOLOGY