ISSN 2285-6064, ISSN CD-ROM 2285-6072, ISSN-L 2285-6064, Online ISSN 2393-5138
 

PREDICTING THE FUTURE TRENDS OF EUROPEAN AND NATIONAL BENCH-MARKS IN THE MANAGEMENT OF BIODEGRADABLE MUNICIPAL WASTE USING ARTIFICIAL NEURAL NETWORKS

Published in Scientific Papers. Series E. Land Reclamation, Earth Observation & Surveying, Environmental Engineering, Vol. XIII
Written by Eda PUNTARIĆ, Lato PEZO, Željka ZGORELEC, Jerko GUNJAČA, Dajana KUČIĆ GRGIĆ, Neven VOĆA

This research employs Artificial Neural Networks (ANN) to develop predictive models for biodegradable municipal waste at both European and national levels. Leveraging socio-demographic and economic data spanning 25 years across 17 European Union (EU) countries, the models aim to forecast biodegradable waste generation over a five-year period. The primary objective is to examine the influence of socio-demographic and economic factors on waste generation. According to the study's findings, it is anticipated that by 2025, the 17 EU countries will produce approximately 67.4 million tons of mixed municipal waste (MMW), 14.7 million tons of municipal paper and cardboard waste (PCW), 6.4 million tons of municipal wood waste (WW), and approximately 0.6 million tons of municipal textile waste (TW). This substantial volume underscores the pressing need for robust infrastructure covering collection, processing, recycling, and disposal mechanisms. The ANN model demonstrated impressive predictive capabilities for MMW, PCW, WW, and TW. Test predictions spanning 2020 to 2025 revealed R2 values ranging between 0.965 and 0.998 during the training phase for the output variables.

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© 2019 SCIENTIFIC PAPERS LAND RECLAMATION, EARTH OBSERVATION & SURVEYING, ENVIRONMENTAL ENGINEERING. All Rights Reserved. To be cited: SCIENTIFIC PAPERS LAND RECLAMATION, EARTH OBSERVATION & SURVEYING, ENVIRONMENTAL ENGINEERING.

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