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For improving the adaptability of the model, the weighted parameter between them is then designed according to the gradient information of image.
Three methods have previously been presented in Computer and Industrial Engineering for the selection of a statistical distribution to describe a data-set: the weighted sum model, the weighted multiplication model and data envelopment analysis.
In the upscaled model, the weighted geometric mean hydraulic conductivity of individual allotments is found to provide the best match to an individual allotment model when comparing total outflow volume and peak flow rate.
A variant of Hidden Markov Model, the weighted Markov Chain Model, has also been applied to classify composers [21].
This model is based on the GAC model, the region-scalable fitting model, the weighted bounded variation model and the active contour model based on the Mumford-Shah model.
This model is inspired by the GAC model, the region-scalable fitting model, the weighted bounded variation model and the active contour model based on the Mumford-Shah model.
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The TFBSs and miRNA target motifs were fed to the Bayesian network model and the models weighted sequence motifs according to their contribution to the expression profiles.
For combinations of a large number of models, the weighted average sometimes provided smaller RMSEs of about 0.01 log units, which was not significantly different compared to the simple average.
Quake works by modeling the weighted multiplicity histogram of k-mers as a combination of two separate distributions (one from erroneous reads, one from accurate reads), and using that model to determine the best cutoff threshold.
We respectively took the FCA method, the classic BN model, and the weighted BN model with the entropy method (Liu 2016) to carry out the same experiment and analyze the results.
In Sections 3 and 4 we present our set of models which we name the Modified Total Variation MPLE model and the Weighted Sobolev MPLE model, respectively.
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