Prediction of methane production in wastewater treatment facility: a data-mining approach

Andrew Kusiak () and Xiupeng Wei ()

Annals of Operations Research, 2014, vol. 216, issue 1, 81 pages

Abstract: A prediction model for methane production in a wastewater processing facility is presented. The model is built by data-mining algorithms based on industrial data collected on a daily basis. Because of many parameters available in this research, a subset of parameters is selected using importance analysis. Prediction results of methane production are presented in this paper. The model performance by different algorithms is measured with five metrics. Based on these metrics, a model built by the Adaptive Neuro-Fuzzy Inference System algorithm has provided most accurate predictions of methane production. Copyright Springer Science+Business Media, LLC 2014

Keywords: Methane production prediction; Wastewater treatment facility; Data-mining algorithms; Neural networks; Adaptive neuro-fuzzy model (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10479-011-1037-6

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