Journal
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume 26, Issue 7, Pages 1643-1651Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2013.04.001
Keywords
Data mining; Pump modeling; Multi-layer perceptron neural network; Time series; Pump scheduling and controlling; Energy consumption
Categories
Funding
- Iowa Energy Center [10-1]
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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. (C) 2013 Elsevier Ltd. All rights reserved.
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