Application of novel hybrid machine learning techniques for particle Froude number estimation in sew...
Application of novel hybrid machine learning techniques for particle Froude number estimation in sewer pipes
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Publisher
Dordrecht: Springer Netherlands
Journal title
Language
English
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Publication information
Publisher
Dordrecht: Springer Netherlands
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Scope and Contents
Contents
The hydraulic capacity of the channel is significantly impacted by the deposition of sediment in sewers and urban drainage systems. Sediment deposition affects a channel's hydraulic capacity in urban drainage and sewage systems. To decrease the effects of this continuous deposition of silt particles, sewer systems frequently have a self-cleaning de...
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Full title
Application of novel hybrid machine learning techniques for particle Froude number estimation in sewer pipes
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Author / Creator
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Record Identifier
TN_cdi_proquest_journals_2793269414
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2793269414
Other Identifiers
ISSN
0921-030X
E-ISSN
1573-0840
DOI
10.1007/s11069-022-05786-x
