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A combination of supervised and random sampling was used to construct model datasets, suitable for algorithm comparison.
A combination of supervised and random sampling was selected to construct reduced size model datasets, suitable for algorithm comparison.
The comparative study of static estimators (soft sensors) for a multicomponent distillation process based on the industrial and calibrated rigorous model datasets is considered.
Our experimental results, based on two 3D model datasets and performance comparisons with other methods, demonstrate the superiority of the SBA method over state-of-the-art methods in terms of 3D model retrieval and classification.
To develop model datasets, 48 leaves from the three varieties were used.
To demonstrate the applicability of the proposed model, datasets from Ighravwe and Oke (2014) were used and complemented with simulated data.
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Extensive experiments are conducted on the ETH-80 dataset and the National Taiwan University 3D model dataset.
A model dataset for UK feed wheat was used to test the GHG emissions calculated by each tool.
The statistical analysis methodologies that are used do not require tracing the history of individual clouds or air parcels; instead they rely on probing the ensemble characteristics of cumulus convection in the large model dataset.
The same tests were also performed using the model dataset.
For example is the data from "ESTJ_5190", the dataset from that user after preprocessing III and splitting to two datasets (model and test), the size of the model dataset is 64 KB.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com