Flores X, Comas J, Roda I R, Jiménez L, Gernaey K V
Laboratory of Chemical and Environmental Engineering (LEQUiA), University of Girona, Campus Montilivi s/n 17071, Girona, Spain.
Water Sci Technol. 2007;56(6):75-83. doi: 10.2166/wst.2007.586.
The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.
本文的主要目的是介绍选定的多变量统计技术在全厂废水处理厂（WWTP）控制策略分析中的应用。在本研究中，聚类分析（CA）、主成分分析/因子分析（PCA/FA）和判别分析（DA）被应用于通过模拟应用于全厂国际水协基准模拟模型2（BSM2）的几种控制策略而获得的评估矩阵数据集。这些技术能够：i）确定具有相似行为的控制策略的自然组或聚类；ii）在数据集中发现并解释隐藏的、复杂的和偶然的关系特征；iii）识别聚类分析所发现的组内重要的判别变量。本研究说明了多变量统计技术对于复杂多标准数据集的分析和解释的有用性，并有助于更有效地利用信息来有效评估控制策略。
