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To take into account variable wind power generation, the Monte Carlo simulation method generates a large number of scenarios which is then reduced by a fast forward algorithm [38].
While our proposed method generates a virtual signal in the audio signal domain, the signal generation in conventional methods is carried out in the power domain [6, 7, 10] or in a higher-order statistical domain [8, 9].
The method generates a new set of variables, called principal components.
This method generates a sequence of feasible points with nonincreasing objective values.
A third method generates a playlist according to user preferences and situations [24].
However, the proposed method generates a PSI identical to the SI on the decoder side.
The concordance method generates a preference ranking which best satisfies a given concordance measure.
Downstream computational analysis of RNA-seq data remains complex because the method generates a staggering amount of data.
The method generates a 24-h weather data file every day.
The proposed method generates a diagnostic signal which indicates possible faults occurring in the GCPV plant.
The method generates a single number that quantifies total pollen influx over the whole exposure time (flowering period).
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