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Description
  • Principal component analysis (PCA) based on singular value decomposition (SVD) of hydrological data was tested for water quality assessment. Using two case studies of waste- and drinking water, PCA via SVD was able to find latent variables which explain 80.8 % and 83.7 % of the variance, respectively. By means of scatter and loading plots, PCA revealed the relationships among samples and hydrochemical parameters which were also confirmed by factor analysis (FA).In the case of wastewater, these latent variables clearly displayed changes of water composition overtime. Drinking water samples were clustered into four groups which were characterized by their typical water composition. On the basis of these results PCA was found to be a suitable technique for water quality assessment.
  • Principal component analysis (PCA) based on singular value decomposition (SVD) of hydrological data was tested for water quality assessment. Using two case studies of waste- and drinking water, PCA via SVD was able to find latent variables which explain 80.8 % and 83.7 % of the variance, respectively. By means of scatter and loading plots, PCA revealed the relationships among samples and hydrochemical parameters which were also confirmed by factor analysis (FA).In the case of wastewater, these latent variables clearly displayed changes of water composition overtime. Drinking water samples were clustered into four groups which were characterized by their typical water composition. On the basis of these results PCA was found to be a suitable technique for water quality assessment. (en)
  • Kvalita pitných a odpadních vod byla hodnocena metodou hlavních komponent na bázi algoritmu SVD. Byly nalezeny latentní proměnné, které charakterizují složení pitných a odpadních vod. Jejich interpretace byla ověřena pomocí faktorové analýzy. (cs)
Title
  • Water quality assessment using SVD-based principal component analysis of hydrological data
  • Hodnocení kvality vody s použitím analýzy hlavních komponent hydrologických dat založené na SVD (cs)
  • Water quality assessment using SVD-based principal component analysis of hydrological data (en)
skos:prefLabel
  • Water quality assessment using SVD-based principal component analysis of hydrological data
  • Hodnocení kvality vody s použitím analýzy hlavních komponent hydrologických dat založené na SVD (cs)
  • Water quality assessment using SVD-based principal component analysis of hydrological data (en)
skos:notation
  • RIV/61989100:27360/05:00012969!RIV06-MSM-27360___
http://linked.open.../vavai/riv/strany
  • 417-422
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM6198910016)
http://linked.open...iv/cisloPeriodika
  • 4
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 551276
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27360/05:00012969
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • water quality; wastewater; drinking water; principal component analysis; singular value decomposition; factor analysis. (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • ZA - Jihoafrická republika
http://linked.open...ontrolniKodProRIV
  • [5FE28387B732]
http://linked.open...i/riv/nazevZdroje
  • Water SA
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 36
http://linked.open...iv/tvurceVysledku
  • Praus, Petr
http://linked.open...n/vavai/riv/zamer
issn
  • 0378-4738
number of pages
http://localhost/t...ganizacniJednotka
  • 27360
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