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This is useful for hydraulic modelling in data scarce flood plain areas, where sharp elevation differences are dominated by man-made elevated elements.
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Consequently, the temperature sensitivity of the accelerometers needs to be modeled in the data processing on-ground.
In recent years he endeavored to successfully model in vivo data using the methods derived from biological engineering.
Approximately 151 billion pairwise genetic effects were modeled in each data set.
Decision tree (DT) is one of the most popular learning models in data mining.
Mobile Agent (MA) technology has been recently proposed in Wireless Sensor Networks (WSNs) literature to answer the scalability problem of client/server model in data fusion applications.
We conclude that wavelet-generalized least squares may be a generally useful estimator of regression models in data complicated by long-memory or fractal noise.
In this section, we review some ranking models in data envelopment analysis.
In this subsection we review the some ranking models in data envelopment analysis.
This agreement shows the excellent ability of this model in data predicting.
Ndomba et al. (2008) intended to validate the Soil and Water Assessment Tool (SWAT) model in data scarce environment.
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