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This data matrix contains the codebook vectors for a 82 x 50 neuron Emergent Self-Organizing Map which describes the multivariate topology of reservoir temperature and geochemical data for 190 samples of produced and geothermal waters from across the United States. Variables included are coordinates derived from reservoir temperature and concentration of Sc, Nd, Pr, Tb, Lu, Gd, Tm, Ce, Yb, Sm, Ho, Er, Eu, Dy, F, alkalinity as bicarbonate, Si, B, Br, Li, Ba, Sr, sulfate, H (derived from pH), K, Mg, Ca, Cl, and Na converted to units of proportion. The concentration data were converted to isometric log-ratio coordinates (following Hron et al., 2010), where the first ratio is Sc serving as the denominator to the geometric...
Agriculture is the leading source of nonpoint-source pollution on a national scale. the driving force of nonpoint-source pollution is the rainfall-runoff process, which is the transformation of rainfall to streamflow. This is a complex, nonlinear, time-varying, and spatially distributed process on the watershed scale that is difficult to effectively model by conventional, deterministic means. Artificial neural networks (ANNs) offer a new approach to forecasting the hydrologic and water quality response of a watershed system. The goal of this work is to develop an ANN model as a long-term forecuating tool for predicting the hydrology and water quality of agricultural watersheds where the physical processes are difficult...
    map background search result map search result map Codebook vectors from a trained emergent self-organizing map displaying multivariate topology of geochemical and reservoir temperature data from produced and geothermal waters of the United States Codebook vectors from a trained emergent self-organizing map displaying multivariate topology of geochemical and reservoir temperature data from produced and geothermal waters of the United States