Wastewater treatment aeration process optimization: A data mining approach.
Being water quality oriented, large-scale industries such as wastewater treatment plants tend to overlook potential savings in energy consumption. Wastewater treatment process includes energy intensive equipment such as pumps and blowers to move and treat wastewater. Presently, a data-driven approac...
| Publicado en: | Journal of Environmental Management Vol. 203; pp. 630 - 640 |
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| Autores principales: | , , , |
| Formato: | Artículo |
| Publicado: |
Academic Press Inc.
Dec2017 Part 2
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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=125057289&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 125057289 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: Dec2017 Part 2 vid: 203 pid: 735 pub: Academic Press Inc. artinfo: ui: 125057289 10.1016/j.jenvman.2016.07.047 ppf: 630 ppct: 10 formats: tig: atl: Wastewater treatment aeration process optimization: A data mining approach. aug: au: Asadi, Ali Verma, Anoop Yang, Kai Mejabi, Ben affil: Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI 48202, United States su: Energy consumption Wastewater treatment Sewage aeration Water quality Data mining sug: subj: Energy consumption Sewage Treatment Facilities Wastewater treatment Sewage aeration Water quality Data mining keyword: Aeration process Data-driven modeling Data-mining Effluents Energy optimization Aeration process Data-driven modeling Data-mining Effluents Energy optimization ab: Being water quality oriented, large-scale industries such as wastewater treatment plants tend to overlook potential savings in energy consumption. Wastewater treatment process includes energy intensive equipment such as pumps and blowers to move and treat wastewater. Presently, a data-driven approach has been applied for aeration process modeling and optimization of one large scale wastewater in Midwest. More specifically, aeration process optimization is carried out with an aim to minimize energy usage without sacrificing water quality. Models developed by data mining algorithms are useful in developing a clear and concise relationship among input and output variables. Results indicate that a great deal of saving in energy can be made while keeping the water quality within limit. Limitation of the work is also discussed. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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