Click on “Download PDF” for the PDF version or on the title for the HTML version. If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options. Exploratory Data Analysis Techniques Applied to Hydrological Time Series. I: Self-Organizing MapsPublished by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org Citation: 21st Century Watershed Technology: Improving Water Quality and Environment Conference Proceedings, 29 March - 3 April 2008, Concepcion, Chile 701P0208cd.(doi:10.13031/2013.24291)Authors: Diego A Rivera, José L Arumí, Mario F Lillo Keywords: groundwater quality, data analysis, clustering, self-organizing maps, Piper Diagram This paper adresses the application of self organizing maps for exploratory porpouses. Self- Organizing Maps allow to explore similarities in a data set collected at different location and/or moment. Two applications of Self- Organizing maps applied to groundwater quality data set are presented: Similary and discriminant capabilities for the identificaction of unknow samples, and the cooperative use with Piper Diagrams for cluster definition. These technique allows a process of exploratory data analysis, knowledge discovery and hypothesis construction rather han hypotesis testing. Also, further applications are discussed. (Download PDF) (Export to EndNotes)
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