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Abstract
This is the second of two papers that describe how data mining can aid natural-resource managers with the difficult problem of controlling the interactions between hydrologic and man-made systems. Data mining is a new science that assists scientists in converting large databases into knowledge, and is uniquely able to leverage the large amounts of real-time, multivariate data now being collected for hydrologic systems. Part 1 gives a high-level overview of data mining, and describes several applications that have addressed major water resource issues in South Carolina. This Part 2 paper describes how various data mining methods are integrated to produce predictive models for controlling surface- and groundwater hydraulics and quality. The methods include: - signal processing to remove noise and decompose complex signals into simpler components; - time series clustering that optimally groups hundreds of signals into "classes" that behave similarly for data reduction and (or) divide-and-conquer problem solving; - classification which optimally matches new data to behavioral classes; - artificial neural networks which optimally fit multivariate data to create predictive models; - model response surface visualization that greatly aids in understanding data and physical processes; and, - decision support systems that integrate data, models, and graphics into a single package that is easy to use.
Study Area
| Publication type | Conference Paper |
|---|---|
| Publication Subtype | Conference Paper |
| Title | Data mining for water resource management part 2 - methods and approaches to solving contemporary problems |
| Year Published | 2010 |
| Language | English |
| Publisher | Clemson University Center for Watershed Excellence |
| Contributing office(s) | South Atlantic Water Science Center |
| Description | 5 p. |
| Larger Work Type | Conference Paper |
| Larger Work Title | Proceedings of the 2010 South Carolina Water Resources Conference |
| Conference Title | 2010 South Carolina Water Resources Conference |
| Conference Location | Columbia, South Carolina |
| Conference Date | October 13-14 2010 |
| Country | United States |
| State | South Carolina |
| Online Only (Y/N) | N |
| Additional Online Files (Y/N) | N |
| Google Analytic Metrics | Metrics page |