Institutional Repository
Technical University of Crete
Technical University of Crete
EN
|
EL
| URI: | http://purl.tuc.gr/dl/dias/EF796372-6386-4C53-BD3F-A58D34B39308 | ||
| Year | 2002 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
| License |
|
||
| Bibliographic Citation | 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 https://doi.org/10.1016/S0921-3449(02)00002-2 | ||
| Appears in Collections |
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.
Copyright © DIAS 2013
