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Real-Time Detection of Sanitary Sewer Overflows Using Neural Networks and Time Series Analysis

Author(s): (Engineer, CH2M-Hill, 2485 Natomas Park Dr., Suite 600, Sacramento, CA 95833; formerly, Graduate Research Assistant, Dept. of Civil Engineering and Engineering Mechanics, The Univ. of Arizona, Tucson, AZ 85721-0072.)
(Engineer, CH2M-Hill, 2485 Natomas Park Dr., Suite 600, Sacramento, CA 95833; formerly, Graduate Research Assistant, Dept. of Civil Engineering and Engineering Mechanics, The Univ. of Arizona, Tucson, AZ 85721-0072.)
(Engineer, CH2M-Hill, 2485 Natomas Park Dr., Suite 600, Sacramento, CA 95833; formerly, Graduate Research Assistant, Dept. of Civil Engineering and Engineering Mechanics, The Univ. of Arizona, Tucson, AZ 85721-0072.)
Medium: journal article
Language(s): English
Published in: Journal of Environmental Engineering (ASCE), , n. 4, v. 133
Page(s): 353-363
DOI: 10.1061/(asce)0733-9372(2007)133:4(353)
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1061/(asce)0733-9372(2007)133:4(353).
  • About this
    data sheet
  • Reference-ID
    10584442
  • Published on:
    08/03/2021
  • Last updated on:
    08/03/2021
 
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