TY - JOUR
T1 - Modeling and analysis of pumps in a wastewater treatment plant
T2 - A data-mining approach
AU - Kusiak, Andrew
AU - Zeng, Yaohui
AU - Zhang, Zijun
PY - 2013/8
Y1 - 2013/8
N2 - A data-mining approach is proposed to model a pumping system in a wastewater treatment plant. Two parameters, energy consumption and wastewater flow rate after the pumping system, are used to evaluate the performance of 27 scenarios while the pump was operating. Five data-mining algorithms are applied to identify the relationships between the outputs (energy consumption and wastewater flow rate) and the inputs (elevation level of the wet well and the speed of the pumps). The accuracy of the flow rate and energy consumption models exceeded 90%. The derived models are deployed to optimize the pump system. The computational results obtained with the proposed models are discussed. © 2013 Elsevier Ltd.
AB - A data-mining approach is proposed to model a pumping system in a wastewater treatment plant. Two parameters, energy consumption and wastewater flow rate after the pumping system, are used to evaluate the performance of 27 scenarios while the pump was operating. Five data-mining algorithms are applied to identify the relationships between the outputs (energy consumption and wastewater flow rate) and the inputs (elevation level of the wet well and the speed of the pumps). The accuracy of the flow rate and energy consumption models exceeded 90%. The derived models are deployed to optimize the pump system. The computational results obtained with the proposed models are discussed. © 2013 Elsevier Ltd.
KW - Data mining
KW - Energy consumption
KW - Multi-layer perceptron neural network
KW - Pump modeling
KW - Pump scheduling and controlling
KW - Time series
UR - http://www.scopus.com/inward/record.url?scp=84878110707&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84878110707&origin=recordpage
U2 - 10.1016/j.engappai.2013.04.001
DO - 10.1016/j.engappai.2013.04.001
M3 - RGC 21 - Publication in refereed journal
SN - 0952-1976
VL - 26
SP - 1643
EP - 1651
JO - Engineering Applications of Artificial Intelligence
JF - Engineering Applications of Artificial Intelligence
IS - 7
ER -
