%0 Journal Article
%T Cluster Analysis to Assess Groundwater Quality in Erode District, Tamil Nadu, India
%A Ganeshbabu Oorkavalan
%A Sashikkumar Madurai Chidambaram
%A Vijayaraj Mariappan
%A Gokulakrishnan Kandaswamy
%A Sakthieswaran Natarajan
%J Circuits and Systems
%P 877-890
%@ 2153-1293
%D 2016
%I Scientific Research Publishing
%R 10.4236/cs.2016.76075
%X Water is a complicated
environment system; traditional methods cannot meet the demands of water
environment protection. As the frontrunner of complex nonlinear science and
artificial intelligence, artificial neural network has begun to be applied in
the field of water quality evaluation and estimation. In view of the deficiency
of the traditional methods, artificial intelligence techniques, such as neural
networks modeling tools, can be applied to assess water quality parameters.
This study is conducted to evaluate factors regulating groundwater quality in
and around Erode District, Tamil Nadu, India. This investigation is focused on
the determination of physico-chemical parameters such as pH, EC, TDS, Ca, Mg,
TH, Na, K, HCO</span><sub><span style=\"font-family:Verdana;\">3</span></sub><span style=\"font-family:Verdana;\">, SO</span><sub><span style=\"font-family:Verdana;\">4</span></sub><span class=\"apple-converted-space\" style=\"font-family:Verdana;\">&nbsp;</span><span style=\"font-family:Verdana;\">and
Cl. Groundwater suitability for drinking, domestic and agricultural purposes is
examined with WHO standards. Dominant factors controlling the
hydro-geochemistry of groundwater in the study area is indicated by Principal
Component Analysis. Classification methods are used to classify the water
quality regulating factors. Cluster analysis is supporting for the grouping on
the basis of contamination characteristics of groundwater quality. This study
also reveals that multivariate statistical analyses are used to improve the
understanding of groundwater condition and appraisal of groundwater quality.
%K Groundwater
%K Water Quality
%K Principal Component Analysis
%K Classification
%K Multilayer Perceptron
%K Dendrogram
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=66545