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Pregled bibliografske jedinice broj: 1020552

Predictive model for municipal waste generation using artificial neural networks—Case study City of Zagreb, Croatia


Ribić, Bojan; Pezo, Lato; Sinčić, Dinko; Lončar, Biljana; Voća, Neven
Predictive model for municipal waste generation using artificial neural networks—Case study City of Zagreb, Croatia // International journal of energy research, 43 (2019), 11; 5701-5713 doi:10.1002/er.4632 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1020552 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Predictive model for municipal waste generation using artificial neural networks—Case study City of Zagreb, Croatia

Autori
Ribić, Bojan ; Pezo, Lato ; Sinčić, Dinko ; Lončar, Biljana ; Voća, Neven

Izvornik
International journal of energy research (0363-907X) 43 (2019), 11; 5701-5713

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Modelling ; neural networks ; sustainability ; waste management

Sažetak
The European Union's environmental legislation related to environmental protection, already implemented in the national legislation of the Republic of Croatia, aims to introduce a system of integrated and sustainable waste management. Within such a system, it is of utmost importance to have a better estimate of the amount of municipal waste generated, which directly influences future planning in the waste management sector. The aim of this research was to develop and optimize models for the estimation of generated municipal waste by application of methodology using neural network models, and taking into account the socio‐economic impact as well as the inputs regarding the actual waste management trends. In this paper, an artificial neural network models were used to predict the municipal waste generation in Zagreb, Croatia. The standardized socio‐economic and waste management variables were chosen to encompass 2013 to 2016 period. Moreover, the test prediction of the observed data was performed for 2017. Developed models sufficiently predicted the quantities of different municipal waste fractions and in that sense can contribute to better planning of upcoming waste management systems that will be sustainable and in order to meet the European Union commitments.

Izvorni jezik
Engleski

Znanstvena područja
Kemijsko inženjerstvo



POVEZANOST RADA


Ustanove:
Fakultet kemijskog inženjerstva i tehnologije, Zagreb,
Agronomski fakultet, Zagreb

Profili:

Avatar Url Neven Voća (autor)

Avatar Url Dinko Sinčić (autor)

Poveznice na cjeloviti tekst rada:

doi

Citiraj ovu publikaciju:

Ribić, Bojan; Pezo, Lato; Sinčić, Dinko; Lončar, Biljana; Voća, Neven
Predictive model for municipal waste generation using artificial neural networks—Case study City of Zagreb, Croatia // International journal of energy research, 43 (2019), 11; 5701-5713 doi:10.1002/er.4632 (međunarodna recenzija, članak, znanstveni)
Ribić, B., Pezo, L., Sinčić, D., Lončar, B. & Voća, N. (2019) Predictive model for municipal waste generation using artificial neural networks—Case study City of Zagreb, Croatia. International journal of energy research, 43 (11), 5701-5713 doi:10.1002/er.4632.
@article{article, author = {Ribi\'{c}, Bojan and Pezo, Lato and Sin\v{c}i\'{c}, Dinko and Lon\v{c}ar, Biljana and Vo\'{c}a, Neven}, year = {2019}, pages = {5701-5713}, DOI = {10.1002/er.4632}, keywords = {Modelling, neural networks, sustainability, waste management}, journal = {International journal of energy research}, doi = {10.1002/er.4632}, volume = {43}, number = {11}, issn = {0363-907X}, title = {Predictive model for municipal waste generation using artificial neural networks—Case study City of Zagreb, Croatia}, keyword = {Modelling, neural networks, sustainability, waste management} }
@article{article, author = {Ribi\'{c}, Bojan and Pezo, Lato and Sin\v{c}i\'{c}, Dinko and Lon\v{c}ar, Biljana and Vo\'{c}a, Neven}, year = {2019}, pages = {5701-5713}, DOI = {10.1002/er.4632}, keywords = {Modelling, neural networks, sustainability, waste management}, journal = {International journal of energy research}, doi = {10.1002/er.4632}, volume = {43}, number = {11}, issn = {0363-907X}, title = {Predictive model for municipal waste generation using artificial neural networks—Case study City of Zagreb, Croatia}, keyword = {Modelling, neural networks, sustainability, waste management} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





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