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Because the prediction procedure is data independent for each basis particle, the MP operation can be easily implemented in parallel.
In a state estimation algorithm, one important procedure is data association, which can be used to determine the relationship between measurements and existing objects.
Further, the gene selection procedure is data driven, thus providing an unbiased approach to knowledge discovery.
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This procedure was data-driven as there was no theoretical basis for selecting variables used in the model.
A pre-requisite to any data mining procedure is a data curation stage [11].
The PRINQUAL procedure is a data transformation procedure that enables nominal and ordinal variables to have optimized covariance or correlation matrix for the following factor analysis.
This procedure is automatic, data-driven and time-variant.
A commonly used assumption behind the data collection procedure is that all the data are fully observed.
This efficient procedure is tested with data of TOPEX/POSEIDON.
Developed procedure is tested by data of a real system.
The procedure is demonstrated with data provided by the Dallas P&DC.
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