A two-stage support-vector-regression optimization model for municipal solid waste management – A case study of Beijing, China
In this study, a two-stage support-vector-regression optimization model (TSOM) is developed for the planning of municipal solid waste (MSW) management in the urban districts of Beijing, China. It represents a new effort to enhance the analysis accuracy in optimizing the MSW management system through...
| Publicado en: | Journal of Environmental Management Vol. 92; no. 12; pp. 3023 - 3038 |
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| Autores principales: | , , |
| Formato: | Case Study |
| Publicado: |
Academic Press Inc.
Dec2011
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=65515381&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 65515381 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03014797 EMJ jtl: Journal of Environmental Management issn: 03014797 maglogo: N pubinfo: dt: Dec2011 vid: 92 iid: 12 pid: 735 pub: Academic Press Inc. artinfo: ui: 65515381 10.1016/j.jenvman.2011.06.038 ppf: 3023 ppct: 15 formats: tig: atl: A two-stage support-vector-regression optimization model for municipal solid waste management – A case study of Beijing, China aug: au: Dai, C. Li, Y.P. Huang, G.H. su: Beijing (China) China Industrial waste management Integer programming Linear programming Support vector machines sug: subj: Beijing (China) China Hazardous Waste Treatment and Disposal Waste treatment and disposal Administration of Air and Water Resource and Solid Waste Management Programs Industrial waste management Integer programming Linear programming Support vector machines keyword: Interval Management Municipal solid waste Optimization Planning Support-vector-regression Uncertainty Interval Management Municipal solid waste Optimization Planning Support-vector-regression Uncertainty ab: In this study, a two-stage support-vector-regression optimization model (TSOM) is developed for the planning of municipal solid waste (MSW) management in the urban districts of Beijing, China. It represents a new effort to enhance the analysis accuracy in optimizing the MSW management system through coupling the support-vector-regression (SVR) model with an interval-parameter mixed integer linear programming (IMILP). The developed TSOM can not only predict the city’s future waste generation amount, but also reflect dynamic, interactive, and uncertain characteristics of the MSW management system. Four kernel functions such as linear kernel, polynomial kernel, radial basis function, and multi-layer perception kernel are chosen based on three quantitative simulation performance criteria [i.e. prediction accuracy (PA), fitting accuracy (FA) and over all accuracy (OA)]. The SVR with polynomial kernel has accurate prediction performance for MSW generation rate, with all of the three quantitative simulation performance criteria being over 96%. Two cases are considered based on different waste management policies. The results are valuable for supporting the adjustment of the existing waste-allocation patterns to raise the city’s waste diversion rate, as well as the capacity planning of waste management system to satisfy the city’s increasing waste treatment/disposal demands. pubtype: Academic Journal doctype: Case Study src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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