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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

Authorized Users Only
2018
Authors
Adamović, Vladimir M.
Antanasijević, Davor
Ćosović, Aleksandar
Ristić, Mirjana
Pocajt, Viktor
Article (Published version)
Metadata
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Abstract
Although the use of municipal solid waste to generate energy can decrease dependency on fossil fuels and consequently reduces greenhouse gases emissions and areas that waste occupies, in many countries municipal solid waste is not recognized as a valuable resource and possible alternative fuel. The aim of this study is to develop a model for the prediction of primary energy production from municipal solid waste in the European countries and then to apply it to the Balkan countries in order to assess their potentials in that field. For this purpose, general regression neural network architecture was applied, and correlation and sensitivity analyses were used for optimisation of the model. The data for 16 countries from the European Union and Norway for the period 2006-2015 was used for the development of the model. The model with the best performance (coefficient of determination R-2 = 0.995 and the mean absolute percentage error MAPE = 7.757%) was applied to the data for the Balkan cou...ntries from 2006 to 2015. The obtained results indicate that there is a significant potential for utilization of municipal solid waste for energy production, which should lead to substantial savings of fossil fuels, primarily lignite which is the most common fossil fuel in the Balkans.

Keywords:
General regression neural network / Energy recovery / Municipal solid waste / Primary production of energy / Fuel substitution / Renewable energy
Source:
Waste Management, 2018, 78, 955-968
Publisher:
  • Pergamon-Elsevier Science Ltd, Oxford
Funding / projects:
  • Development and Application of Methods and Materials for Monitoring New Organic Contaminants, Toxic Compounds and Heavy Metals (RS-172007)

DOI: 10.1016/j.wasman.2018.07.012

ISSN: 0956-053X

PubMed: 32559992

WoS: 000444660600101

Scopus: 2-s2.0-85049652127
[ Google Scholar ]
21
14
URI
http://TechnoRep.tmf.bg.ac.rs/handle/123456789/3840
Collections
  • Radovi istraživača / Researchers’ publications (TMF)
Institution/Community
Tehnološko-metalurški fakultet
TY  - JOUR
AU  - Adamović, Vladimir M.
AU  - Antanasijević, Davor
AU  - Ćosović, Aleksandar
AU  - Ristić, Mirjana
AU  - Pocajt, Viktor
PY  - 2018
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/3840
AB  - Although the use of municipal solid waste to generate energy can decrease dependency on fossil fuels and consequently reduces greenhouse gases emissions and areas that waste occupies, in many countries municipal solid waste is not recognized as a valuable resource and possible alternative fuel. The aim of this study is to develop a model for the prediction of primary energy production from municipal solid waste in the European countries and then to apply it to the Balkan countries in order to assess their potentials in that field. For this purpose, general regression neural network architecture was applied, and correlation and sensitivity analyses were used for optimisation of the model. The data for 16 countries from the European Union and Norway for the period 2006-2015 was used for the development of the model. The model with the best performance (coefficient of determination R-2 = 0.995 and the mean absolute percentage error MAPE = 7.757%) was applied to the data for the Balkan countries from 2006 to 2015. The obtained results indicate that there is a significant potential for utilization of municipal solid waste for energy production, which should lead to substantial savings of fossil fuels, primarily lignite which is the most common fossil fuel in the Balkans.
PB  - Pergamon-Elsevier Science Ltd, Oxford
T2  - Waste Management
T1  - 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
EP  - 968
SP  - 955
VL  - 78
DO  - 10.1016/j.wasman.2018.07.012
ER  - 
@article{
author = "Adamović, Vladimir M. and Antanasijević, Davor and Ćosović, Aleksandar and Ristić, Mirjana and Pocajt, Viktor",
year = "2018",
abstract = "Although the use of municipal solid waste to generate energy can decrease dependency on fossil fuels and consequently reduces greenhouse gases emissions and areas that waste occupies, in many countries municipal solid waste is not recognized as a valuable resource and possible alternative fuel. The aim of this study is to develop a model for the prediction of primary energy production from municipal solid waste in the European countries and then to apply it to the Balkan countries in order to assess their potentials in that field. For this purpose, general regression neural network architecture was applied, and correlation and sensitivity analyses were used for optimisation of the model. The data for 16 countries from the European Union and Norway for the period 2006-2015 was used for the development of the model. The model with the best performance (coefficient of determination R-2 = 0.995 and the mean absolute percentage error MAPE = 7.757%) was applied to the data for the Balkan countries from 2006 to 2015. The obtained results indicate that there is a significant potential for utilization of municipal solid waste for energy production, which should lead to substantial savings of fossil fuels, primarily lignite which is the most common fossil fuel in the Balkans.",
publisher = "Pergamon-Elsevier Science Ltd, Oxford",
journal = "Waste Management",
title = "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",
pages = "968-955",
volume = "78",
doi = "10.1016/j.wasman.2018.07.012"
}
Adamović, V. M., Antanasijević, D., Ćosović, A., Ristić, M.,& Pocajt, V.. (2018). 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. in Waste Management
Pergamon-Elsevier Science Ltd, Oxford., 78, 955-968.
https://doi.org/10.1016/j.wasman.2018.07.012
Adamović VM, Antanasijević D, Ćosović A, Ristić M, Pocajt V. 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. in Waste Management. 2018;78:955-968.
doi:10.1016/j.wasman.2018.07.012 .
Adamović, Vladimir M., Antanasijević, Davor, Ćosović, Aleksandar, Ristić, Mirjana, Pocajt, Viktor, "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" in Waste Management, 78 (2018):955-968,
https://doi.org/10.1016/j.wasman.2018.07.012 . .

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