Multivariate classification and modeling in surface water pollution estimation

被引：54

作者：

Astel, A. ^{[1
]}

Tsakovski, S. ^{[2
]}

Simeonov, V. ^{[2
]}

Reisenhofer, E. ^{[3
]}

Piselli, S. ^{[4
]}

Barbieri, P. ^{[3
]}

机构：

[1] Pomeranian Acad, Environm Chem Res Unit, Biol & Environm Protect Inst, PL-76200 Slupsk, Poland

[2] Univ Sofia St Kl Okhridski, Fac Chem, Sofia 1164, Bulgaria

[3] Univ Trieste, Dept Chem Sci, I-34127 Trieste, Italy

[4] ACEGAS APS, I-34123 Trieste, Italy

来源：

ANALYTICAL AND BIOANALYTICAL CHEMISTRY | 2008年 / 390卷 / 05期

关键词：

chemometrics; surface water; N-way PCA; SOM; City of Trieste;

D O I：

10.1007/s00216-007-1700-6

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

The present study deals with the application of self-organizing maps (SOM) and multiway principal-components analysis to classify, model, and interpret a large monitoring data set for surface water quality. The chemometric methods applied made it possible to reveal specific quality patterns of the chemical and biological parameters used to monitor the water quality (relation between water temperature, turbidity, hardness, colibacteria), seasonal impacts during the long period of observation and the relative independence on the spatial location of the sampling sites (water supply sources for the City of Trieste).

引用

页码：1283 / 1292

页数：10

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