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Ιδρυματικό Αποθετήριο [SANDBOX]
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| URI | http://purl.tuc.gr/dl/dias/EF796372-6386-4C53-BD3F-A58D34B39308 | - |
| Αναγνωριστικό | https://doi.org/10.1016/S0921-3449(02)00002-2 | - |
| Αναγνωριστικό | http://www.sciencedirect.com/science/article/pii/S0921344902000022 | - |
| Γλώσσα | en | - |
| Μέγεθος | 14 pages | en |
| Τίτλος | Time series analysis and forecasting techniques for municipal solid waste management | en |
| Δημιουργός | Navarro Esbrí, Joaquín | en |
| Δημιουργός | Diamantopoulos Evaggelos | en |
| Δημιουργός | Διαμαντοπουλος Ευαγγελος | el |
| Δημιουργός | Ginestar Damian | en |
| Εκδότης | Elsevier | en |
| Περίληψη | Successful planning and operation of a solid waste management system depends on municipal solid waste (MSW) generation process knowledge and on accurate predictions of solid waste quantities produced. Conventional analysis and prediction models are based on demographic and socioeconomic factors. However, this kind of analysis is related to mean generation data. Dynamic MSW generation analysis can be done using time series data of solid waste generated quantities. In this paper some tools for time series analysis and forecasting are proposed to study MSW generation. A prediction technique based on non-linear dynamics is proposed, comparing its performance with a seasonal AutoRegressive and Moving Average (sARIMA) methodology, dealing with short and medium term forecasting. Finally, a practical implementation consisting of the study of MSW time series of three cities in Spain and Greece is presented. | en |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2015-11-18 | - |
| Ημερομηνία Δημοσίευσης | 2002 | - |
| Θεματική Κατηγορία | Waste management industry | en |
| Θεματική Κατηγορία | refuse disposal industry | en |
| Θεματική Κατηγορία | waste management industry | en |
| Βιβλιογραφική Αναφορά | J. Navarro-Esbrı́, E. Diamadopoulos and D. Ginestar, "Time series analysis and forecasting techniques for municipal solid waste management," Resour. Conserv. Recycl., vol. 35, no. 3, pp. 201-214, June 2002. doi: 10.1016/S0921-3449(02)00002-2 | en |
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