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Estimation of NMVOC emissions using artificial neural networks and economical and sustainability indicators as inputs
(Springer Heidelberg, Heidelberg, 2016)
This paper describes the development of an artificial neural network (ANN) model based on economical and sustainability indicators for the prediction of annual non-methane volatile organic compounds (NMVOCs) emissions in ...
Application of experimental design for the optimization of artificial neural network-based water quality model: a case study of dissolved oxygen prediction
(Springer Heidelberg, Heidelberg, 2018)
This paper presents an application of experimental design for the optimization of artificial neural network (ANN) for the prediction of dissolved oxygen (DO) content in the Danube River. The aim of this research was to ...
Modeling of ammonia emission in the USA and EU countries using an artificial neural network approach
(Springer Heidelberg, Heidelberg, 2015)
Ammonia emissions at the national level are frequently estimated by applying the emission inventory approach, which includes the use of emission factors, which are difficult and expensive to determine. Emission factors are ...