Modeling and analysis of pumps in a wastewater treatment plant : A data-mining approach
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 1643-1651 |
| Journal / Publication | Engineering Applications of Artificial Intelligence |
| Volume | 26 |
| Issue number | 7 |
| Publication status | Published - Aug 2013 |
Link(s)
Abstract
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.
Research Area(s)
- Data mining, Energy consumption, Multi-layer perceptron neural network, Pump modeling, Pump scheduling and controlling, Time series
Citation Format(s)
Modeling and analysis of pumps in a wastewater treatment plant: A data-mining approach. / Kusiak, Andrew; Zeng, Yaohui; Zhang, Zijun.
In: Engineering Applications of Artificial Intelligence, Vol. 26, No. 7, 08.2013, p. 1643-1651.
In: Engineering Applications of Artificial Intelligence, Vol. 26, No. 7, 08.2013, p. 1643-1651.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
