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So, this model combination is considered for the experimental study.
This method of model combination is similar to convolving the current model with the input model.
Our training methodology includes multi-channel noisy data training and speaker adaptive training, whereas at test time model combination is used to improve generalization.
Model combination is often used when several applicable algorithms for a problem are available.
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The mean accuracy for each marker set-imputation method-prediction model combination was computed.
Each dataset was run for 200,000,000 generations using two different clock models (strict and uncorrelated lognormal) and three different demographic models (constant, exponential, and Bayesian skyline).The best-fitting clock/demographic model combination was determined using Bayes factors as implemented in Tracer v1.5 [ 65].
Sensitivity analysis of different model combinations is carried out by using ORNL 19-pin benchmark test.
Different model combinations are considered to select the best model that gives better recognition accuracy.
Prior to the assessment of future change, the selected model combinations were evaluated against observations in the period 2001 2010 for a number of river basins.
To define activity and selectivity mechanisms of chosen catalysts in hydrogenation process model combinations are often used such as anthracene, phenanthrene, pyrene, naphthalene, and others, which allow establishing more detailed mechanism of heavy hydrocarbon refinement and scientifically developing vindicated methods for forecasting their management.
Based on this mathematical model, the combination is considered synergistic when the CI<1.0 and is highly synergistic when the CI<0.5.
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