Pretraživanje
Prikaz rezultata 1-10 od 22
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 ...
The geochemistry model of the surface sediment determined by using ED-XRF technique: a case study of the Boka Kotorska bay, Adriatic Sea
(Springer Heidelberg, Heidelberg, 2016)
The spatial distribution of major oxides (Na2O, K2O, SiO2, Al2O3, Fe2O3, CaO, MgO, MnO, TiO2, P2O5) and numerous elements (Cr, Co, Ni, Cu, Zn, As, Se, Pb, Sn, Sb, Ba, Sr, Br, Rb, Zr, Mo, Cs, Y, V, Ga, La, U, Th, Nb, W, Sc, ...
Modelling of dissolved oxygen content using artificial neural networks: Danube River, North Serbia, case study
(Springer Heidelberg, Heidelberg, 2013)
The aims of this study are to create an artificial neural network (ANN) model using non-specific water quality parameters and to examine the accuracy of three different ANN architectures: General Regression Neural Network ...
Migration of cypermethrin to and through the PET containers and artificial neural network-based estimation of its emission
(Springer Verlag, 2019)
Nowadays, the extensive use of pesticides in crops production puts a significant challenge to minimize its side effects along with safe production, storage, and after-use treatment. This paper reports results related to ...
Prediction of municipal solid waste generation using artificial neural network approach enhanced by structural break analysis
(Springer Heidelberg, Heidelberg, 2017)
This paper presents the development of a general regression neural network (GRNN) model for the prediction of annual municipal solid waste (MSW) generation at the national level for 44 countries of different size, population ...
Solid-phase extraction of multi-class pharmaceuticals from environmental water samples onto modified multi-walled carbon nanotubes followed by LC-MS/MS
(Springer Heidelberg, Heidelberg, 2017)
In this paper, pristine and chemically treated multi-walled carbon nanotubes (MWCNTs) were employed as solid-phase extraction sorbents for the isolation and enrichment of multi-class pharmaceuticals from the surface water ...
Artificial neural network modelling of biological oxygen demand in rivers at the national level with input selection based on Monte Carlo simulations
(Springer Heidelberg, Heidelberg, 2015)
Biological oxygen demand (BOD) is the most significant water quality parameter and indicates water pollution with respect to the present biodegradable organic matter content. European countries are therefore obliged to ...
Sorption of selected pharmaceuticals and pesticides on different river sediments
(Springer Heidelberg, Heidelberg, 2016)
In the present work, the sorption ability of 17 pharmaceutical compounds, two metabolites, and 15 pesticides (34 target compounds in total) onto four different river sediments was investigated separately. Selected compounds ...
The impacts of seawater physicochemical parameters and sediment metal contents on trace metal concentrations in musselsa chemometric approach
(Springer Heidelberg, Heidelberg, 2018)
The concentrations of Al, Ba, Cd, Co, Cr, Cu, Fe, Li, Mn, Ni, Pb, Sr, Zn, and Hg were studied in Mytilus galloprovincialis collected from the coastal area of Montenegro. The impact of seawater temperature, salinity, dissolved ...
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 ...