Journal article
A data-driven model for maximization of methane production in a wastewater treatment plant
Water science and technology, Vol.65(6), pp.1116-1122
03/01/2012
DOI: 10.2166/wst.2012.953
PMID: 22378011
Abstract
A data-driven approach for maximization of methane production in a wastewater treatment plant is presented. Industrial data collected on a daily basis was used to build the model. Temperature, total solids, volatile solids, detention time and pH value were selected as parameters for the model construction. First, a prediction model of methane production was built by a multi-layer perceptron neural network. Then a particle swarm optimization algorithm was used to maximize methane production based on the model developed in this research. The model resulted in a 5.5% increase in methane production.
Details
- Title: Subtitle
- A data-driven model for maximization of methane production in a wastewater treatment plant
- Creators
- Andrew Kusiak - Department of Mechanical and Industrial Engineering, 2139 Seamans Center, The University of Iowa, Iowa City, IA 52242, USAXiupeng Wei - Department of Mechanical and Industrial Engineering, 3131 Seamans Center, The University of Iowa, Iowa City, IA 52242, USA
- Resource Type
- Journal article
- Publication Details
- Water science and technology, Vol.65(6), pp.1116-1122
- DOI
- 10.2166/wst.2012.953
- PMID
- 22378011
- ISSN
- 0273-1223
- eISSN
- 1996-9732
- Language
- English
- Date published
- 03/01/2012
- Academic Unit
- Industrial and Systems Engineering; Nursing
- Record Identifier
- 9984064213202771
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