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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.
Consider a variational model in data assimilation as follows: Assume that (u_{R}) is the remote sensing observed value.
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.
The obtained results, considering different performance measures, not only suggest this approach improves the quality of a database with missing values, but also the best results are clearly obtained using the Multilayer Perceptron model in data sets with categorical variables.
Albeit being versatile for varied electrochemical systems and powerful in distinguishing multiple processes in a wide frequency spectrum, the EIS method usually needs a physical model in data analysis; misuse of models leads researchers to provide unwarranted interpretation of EIS data.
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This problem is challenging, especially when skipping the step of building an explicit state-space plant model in data-driven design, because the inverse of the underlying plant dynamics is required and needs to be stable.
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.
Decision tree (DT) is one of the most popular learning models in data mining.
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.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
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CEO of Professional Science Editing for Scientists @ prosciediting.com