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

The Science of the total environment, 2013-01, Vol.443, p.511-519

2013

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Multilevel split of high-dimensional water quality data using artificial neural networks for the prediction of dissolved oxygen in the Danube River

Neural computing & applications, 2020-04, Vol.32 (8), p.3957-3966

2020

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An artificial neural network approach for the estimation of the primary production of energy from municipal solid waste and its application to the Balkan countries

Waste management (Elmsford), 2018-08, Vol.78, p.955-968

2018

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

International journal of greenhouse gas control, 2014-01, Vol.20, p.244-253

2014

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Prediction of municipal solid waste generation using artificial neural network approach enhanced by structural break analysis

Environmental science and pollution research international, 2017, Vol.24 (1), p.299-311

2017

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forecasting of municipal waste generation using artificial neural networks and sustainability indicators

Sustainability science, 2013, Vol.8 (1), p.37-46

2013

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An optimized artificial neural network model for the prediction of rate of hazardous chemical and healthcare waste generation at the national level

Journal of material cycles and waste management, 2018-07, Vol.20 (3), p.1736-1750

2018

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Modeling of methane emissions using artificial neural network approach

Journal of the Serbian Chemical Society, 2015-01, Vol.80 (3), p.421-433

2015

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Modeling the BOD of Danube River in Serbia using spatial, temporal, and input variables optimized artificial neural network models

Environmental monitoring and assessment, 2016-05, Vol.188 (5), p.300-300, Article 300

2016

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Prediction of nitrogen oxides emissions at the national level based on optimized artificial neural network model

Air quality, atmosphere and health, 2017, Vol.10 (1), p.15-23

2017

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Estimation of NMVOC emissions using artificial neural networks and economical and sustainability indicators as inputs

Environmental science and pollution research international, 2016-06, Vol.23 (11), p.10753-10762

2016

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Forecasting human exposure to PM10 at the national level using an artificial neural network approach

Journal of chemometrics, 2013-06, Vol.27 (6), p.170-177

2013

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

Environmental science and pollution research international, 2015-12, Vol.22 (23), p.18849-18858

2015

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Modelling of dissolved oxygen in the Danube River using artificial neural networks and Monte Carlo Simulation uncertainty analysis

Journal of hydrology (Amsterdam), 2014-11, Vol.519, p.1895-1907

2014

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A differential multi-criteria analysis for the assessment of sustainability performance of European countries: Beyond country ranking

Journal of cleaner production, 2017-11, Vol.165, p.213-220

2017

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A linear and non-linear polynomial neural network modeling of dissolved oxygen content in surface water: Inter- and extrapolation performance with inputs' significance analysis

The Science of the total environment, 2018-01, Vol.610-611, p.1038-1046

2018

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A model for cross-referencing and calculating similarity of metal alloys

Metallurgical & materials engineering, 2013-12, Vol.19 (4), p.295-306

2013

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Modeling of energy consumption and related GHG (greenhouse gas) intensity and emissions in Europe using general regression neural networks

Energy (Oxford), 2015-05, Vol.84, p.816-824

2015

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Urban population exposure to tropospheric ozone: A multi-country forecasting of SOMO35 using artificial neural networks

Environmental pollution (1987), 2019-01, Vol.244, p.288-294

2019

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Analysis of selected elements in water in the drinking water preparation plants in Belgrade, Serbia

Hemijska industrija, 2011-01, Vol.65 (2), p.187-196

2011

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Prediction of the transition temperature of bent-core liquid crystals using fuzzy “digital thermometer” model based on artificial neural networks

Engineering applications of artificial intelligence, 2018-05, Vol.71, p.251-258

2018

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Modelling of dissolved oxygen content using artificial neural networks: Danube River, North Serbia, case study

Environmental science and pollution research international, 2013-12, Vol.20 (12), p.9006-9013

2013

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Determination of heavy metal concentrations in tea samples taken from Belgrade market, Serbia

Hemijska industrija, 2009, Vol.63 (5), p.433-436

2009

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Multiple-input–multiple-output general regression neural networks model for the simultaneous estimation of traffic-related air pollutant emissions

Atmospheric pollution research, 2018-03, Vol.9 (2), p.388-397

2018

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Specifying cases for technology enhanced learning in a small and medium enterprise

Knowledge management & e-learning, 2010-09, Vol.2 (3), p.260-277

2010

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

Multilevel split of high-dimensional water quality data using artificial neural networks for the prediction of dissolved oxygen in the Danube River

An artificial neural network approach for the estimation of the primary production of energy from municipal solid waste and its application to the Balkan countries

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

Prediction of municipal solid waste generation using artificial neural network approach enhanced by structural break analysis

forecasting of municipal waste generation using artificial neural networks and sustainability indicators

An optimized artificial neural network model for the prediction of rate of hazardous chemical and healthcare waste generation at the national level

Modeling of methane emissions using artificial neural network approach

Modeling the BOD of Danube River in Serbia using spatial, temporal, and input variables optimized artificial neural network models

Prediction of nitrogen oxides emissions at the national level based on optimized artificial neural network model

Estimation of NMVOC emissions using artificial neural networks and economical and sustainability indicators as inputs

Forecasting human exposure to PM10 at the national level using an artificial neural network approach

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

Modelling of dissolved oxygen in the Danube River using artificial neural networks and Monte Carlo Simulation uncertainty analysis

A differential multi-criteria analysis for the assessment of sustainability performance of European countries: Beyond country ranking

A linear and non-linear polynomial neural network modeling of dissolved oxygen content in surface water: Inter- and extrapolation performance with inputs' significance analysis

A model for cross-referencing and calculating similarity of metal alloys

Modeling of energy consumption and related GHG (greenhouse gas) intensity and emissions in Europe using general regression neural networks

Urban population exposure to tropospheric ozone: A multi-country forecasting of SOMO35 using artificial neural networks

Analysis of selected elements in water in the drinking water preparation plants in Belgrade, Serbia

Prediction of the transition temperature of bent-core liquid crystals using fuzzy “digital thermometer” model based on artificial neural networks

Modelling of dissolved oxygen content using artificial neural networks: Danube River, North Serbia, case study

Determination of heavy metal concentrations in tea samples taken from Belgrade market, Serbia

Multiple-input–multiple-output general regression neural networks model for the simultaneous estimation of traffic-related air pollutant emissions

Specifying cases for technology enhanced learning in a small and medium enterprise

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