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

被引：40

作者：

Kusiak, Andrew ^{[1
]}

Wei, Xiupeng ^{[1
]}

机构：

[1] Univ Iowa, Dept Mech & Ind Engn, Seamans Ctr 3131, Iowa City, IA 52242 USA

来源：

ANNALS OF OPERATIONS RESEARCH | 2014年 / 216卷 / 01期

关键词：

Methane production prediction; Wastewater treatment facility; Data-mining algorithms; Neural networks; Adaptive neuro-fuzzy model; ANAEROBIC-DIGESTION; OPTIMIZATION; DESIGN; MODEL;

D O I：

10.1007/s10479-011-1037-6

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 [运筹学与控制论]; 120117 [社会管理工程];

摘要：

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.

引用

页码：71 / 81

页数：11

共 28 条

[1]

Using genetic algorithms to optimize nearest neighbors for data mining [J].