Selecting the most relevant variables for anaerobic digestion imbalances: Two case studies
dc.contributor.author
dc.date.accessioned
2014-09-25T07:57:30Z
dc.date.available
2014-09-25T07:57:30Z
dc.date.issued
2010-06-01
dc.identifier.issn
1061-4303
1061-4303
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dc.description.abstract
In this study, a wrapper approach was applied to objectively select the most important variables related to two different anaerobic digestion imbalances, acidogenic states and foaming. This feature selection method, implemented in artificial neural networks (ANN), was performed using input and output data from a fully instrumented pilot plant (1 m 3 upflow fixed bed digester). Results for acidogenic states showed that pH, volatile fatty acids, and inflow rate were the most relevant variables. Results for foaming showed that inflow rate and total organic carbon were among the relevant variables, both of which were related to the feed loading of the digester. Because there is not a complete agreement on the causes of foaming, these results highlight the role of digester feeding patterns in the development of foaming
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application/pdf
dc.language.iso
eng
dc.publisher
Water Environment Federation
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Reproducció digital del document publicat a: http://dx.doi.org/10.2175/106143009X12529484815359
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© Water Environment Research, 2010, vol. 82, p. 492-498
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Articles publicats (D-EQATA)
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Tots els drets reservats
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dc.title
Selecting the most relevant variables for anaerobic digestion imbalances: Two case studies
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.embargo.terms
Cap
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
012533
dc.identifier.eissn
1554-7531