Extraction of a Parameter as an Index to Assess Water Quality of the Tamagawa, Tokyo, Japan, by Using Neural Networks and Multivariate Analysis

Parameters as an index to efficiently assess the pollution level of the upper, middle, and lower streams of the Tamagawa (Tokyo, Japan) based on measured water quality were determined by using multivariate analysis, principal component analysis (PCA), and cluster analysis (CA) for data measured from...

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Bibliographic Details
Published inJournal of Computer Chemistry, Japan Vol. 6; no. 1; pp. 19 - 26
Main Authors KAMBE, Junko, AOYAMA, Tomoo, YAMAUCHI, Aiko, NAGASHIMA, Umpei
Format Journal Article
LanguageEnglish
Published Tokyo Society of Computer Chemistry, Japan 01.01.2007
Japan Science and Technology Agency
Subjects
Chemometrics
Cluster Analysis
Principal Component Analysis
Tamagawa
Water Contamination
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Summary:Parameters as an index to efficiently assess the pollution level of the upper, middle, and lower streams of the Tamagawa (Tokyo, Japan) based on measured water quality were determined by using multivariate analysis, principal component analysis (PCA), and cluster analysis (CA) for data measured from 1994 to 2002. Missing data during 2000-2002 were estimated using a perceptron type neural network and arithmetic progression. The combination of scores for the first and second principal components obtained by PCA enabled classification of the upper, middle, and lower streams of the Tamagawa. The CA results corresponded well with the PCA results. Based on the score of the first principal compornent determined here, contributions to the water pollution of the middle and lower streams should be decreased to improve the water quality of the Tamagawa.
ISSN:1347-1767
1347-3824
DOI:10.2477/jccj.6.19