TY - GEN
T1 - A neural network based classification scheme for sorting sources and ages of fecal contamination in water
AU - Brion, Gail M.
AU - Lingireddy, Srinivasa
AU - Neelakantan, T. R.
PY - 2005
Y1 - 2005
N2 - Artificial neural network (ANN) modeling that used a set of simple bacterial measurements and informational inputs was successfully applied to data observations from a small watershed for the purposes of distinguishng between human sewage and animal-impacted runoff, fresh runoff from aged, and agricultural land use associated fresh runoff from that of suburban land-use associated fresh runoff. The ANN approach was able to classify sewage from heavily contaminated runoff with greater than 99% accuracy. Turbidity was found to be relatively unimportant as an input variable for sorting sewage from runoff, while gross measurements of gram-negative and gram-positive bacteria were required. ANN classification of aged suburban runoff from fresh, and agricultural runoff from suburban was accomplished with greater than 90% accuracy. Copyright ASCE 2005.
AB - Artificial neural network (ANN) modeling that used a set of simple bacterial measurements and informational inputs was successfully applied to data observations from a small watershed for the purposes of distinguishng between human sewage and animal-impacted runoff, fresh runoff from aged, and agricultural land use associated fresh runoff from that of suburban land-use associated fresh runoff. The ANN approach was able to classify sewage from heavily contaminated runoff with greater than 99% accuracy. Turbidity was found to be relatively unimportant as an input variable for sorting sewage from runoff, while gross measurements of gram-negative and gram-positive bacteria were required. ANN classification of aged suburban runoff from fresh, and agricultural runoff from suburban was accomplished with greater than 90% accuracy. Copyright ASCE 2005.
UR - http://www.scopus.com/inward/record.url?scp=37249008141&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=37249008141&partnerID=8YFLogxK
U2 - 10.1061/40792(173)325
DO - 10.1061/40792(173)325
M3 - Conference contribution
AN - SCOPUS:37249008141
SN - 0784407924
SN - 9780784407929
T3 - World Water Congress 2005: Impacts of Global Climate Change - Proceedings of the 2005 World Water and Environmental Resources Congress
SP - 325
BT - World Water Congress 2005
T2 - 2005 World Water and Environmental Resources Congress
Y2 - 15 May 2005 through 19 May 2005
ER -
