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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 ...
Nanoscale zerovalent iron (nZVI) supported by natural and acid-activated sepiolites: the effect of the nZVI/support ratio on the composite properties and Cd2+ adsorption
(Springer Heidelberg, Heidelberg, 2017)
Natural (SEP) and partially acid-activated (AAS) sepiolites were used to prepare composites with nanoscale zerovalent iron (nZVI) at different (SEP or AAS)/nZVI ratios in order to achieve the best nZVI dispersibility and ...
Distribution and mobility of heavy elements in floodplain agricultural soils along the Ibar River (Southern Serbia and Northern Kosovo). Chemometric investigation of pollutant sources and ecological risk assessment
(Springer Heidelberg, Heidelberg, 2016)
This work investigates the influence of a high-magnitude flood event on heavy elements (HEs) pollution and mobility in the agricultural soils along Ibar River in Southern Serbia and Northern Kosovo. The study area was one ...
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 ...
Characterization of PM(2.5)sources in a Belgrade suburban area: a multi-scale receptor-oriented approach
(Springer Heidelberg, Heidelberg, 2020)
Designated as the most harmful for health, PM(2.5)aerosol fraction was a subject of our study. It was collected for all four seasons during 2014/15 in the suburban area of Belgrade (Serbia) and analysed for Al, Si, P, S, ...
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 ...
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 ...
Non-thermal plasma and ultrasound-assisted open lactic acid fermentation of distillery stillage
(Springer Heidelberg, Heidelberg, 2019)
Stillage is the main by-product of bioethanol production and the cost of its treatment significantly affects the economy of bioethanol production. A process of thermal sterilization before lactic acid fermentation (LAF) ...
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 ...
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 ...