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Finally, using a fuzzy score matrix has benefits in case of MOQ which have order steps and could be answered by different ways.
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By scoring indicators using a fuzzy logic scale, we were able to avoid hard decision thresholds, which can lead to abrupt transitions in assessment scores.
For the second step, regulation programs are learned using a fuzzy decision tree model.
This assignment is learned using a fuzzy decision tree model.
Genes were clustered according to their temporal profiles using a fuzzy c-means algorithm.
In the second stage all criteria were standardized using a fuzzy set.
The genes were clustered using a "fuzzy k-means clustering" into 10 major clusters.
At this level, experimental quantitative properties of amino acids are assigned to their identities using a fuzzy mapping.
The first phase uses a fuzzy conflict graph to build an initial fragment partition.
In the ROI extraction procedure, we use a fuzzy stretching algorithm to enhance the brightness contrast.
In this study, we used a fuzzy neural network (FNN) in a bioinformatics approach to search for complex risk characteristics.
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