Sentence examples for methods for benchmarking from inspiring English sources

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For the above mentioned reasons, we do not consider any of the miscellaneous methods for benchmarking.

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We describe our method for benchmarking Semantic Web knowledge base systems with respect to use in large OWL applications.

While several previous studies [16, 30, 39, 43] compared several algorithms, they did not use a widely accepted audio classification method for benchmarking their neural networks.

According to Song et al. [38], DEA is a method for benchmarking production units' productivity, profitability or any other criteria that could be assessed based on the available input and output variables.

It should be considered a potentially valuable adjunct method for benchmarking complex health policy goals such as those for chronic disease.

In short, the QCA method presents as a possibly valuable small- N adjunct method for benchmarking, rather than a singular solution to the challenges that beset a measurement-minded age.

The AP method was chosen for benchmarking, because Chen and Reynolds (2002) showed that it outperforms other 2D structural descriptor-based similarity measures, such as the approach based on Molecular ACCess System (MACCS) keys proposed by Molecular Design Limited (MDL).

Further developments in medical documentation standards, in particular HL7 clinical document architecture (CDA) [ 8] with its clinical document code, will facilitate methods for HIS benchmarking.

These cannot be used for benchmarking methods that aim at the prioritization of candidates for polygenic diseases.

Finally, it should be noted that the utility of this collection goes beyond parameter estimation: the models provided here can also be used for benchmarking methods for optimal experimental design, identifiability analysis, sensitivity analysis, model reduction, and in the case of metabolic models also for metabolic engineering purposes.

Other perspective directions include modeling of coevolution as a system of stochastic processes, low-polynomial methods of simultaneous phylogeny and alignment construction, and applying mathematically proved methods to simulate test datasets for benchmarking phylogenetic algorithms.

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