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The selected algorithm is now part of ROMS_AGRIF.
Our results indicate that the selected algorithm, applied to land cover classes, can provide reliable data, especially when referring to classes with homogeneous texture properties and surface reflectance.
The selected algorithm, called Approximate Block Newton, is actually a version of the Jacobian-free Newton Krylov method suitably modified for coupling mono-disciplinary solvers.
With this grouping process, performed hierarchically, and depending on the selected algorithm, multiple clustering options are possible.
The facies modeling used the upscaled lithology data and distributes these data across the area and between the wells using a selected algorithm.
The selected algorithm, as well as other operations present in the low- and mid-level image-processing stages, matches well with this kind of architectures.
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Empirical results show that our proposed algorithms are efficient and outperform the selected algorithms in most cases, and show the superiority of our proposed feature selection framework.
Next, the selected algorithms implemented in the fault detection operation are briefly described.
Results of the performance obtained are presented highlighting the differences among various configurations running the selected algorithms.
All the selected algorithms are tested with the consideration of essential home appliances in Real Time Pricing (RTP) environment.
The comparison demonstrates the superiority of the CUSUM algorithms against other selected algorithms in reducing detection delay while maintaining an acceptable detection rate.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com