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Section ' Results' describes the key points of data fusion and imputation methods.
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The databases were searched using the two types of data fusion: similarity fusion (SF) and group fusion (GF).
Two examples of classes of fusion systems formalized in the paper are data fusion and decision fusion; decision fusion is shown to be a subclass of data fusion.
E agr is the energy consumption of data fusion.
Furthermore, they did not address the issue of data fusion.
This idea of data fusion is also pursued by C.
Statistically combining two, relatively distinct, data sources is the goal of data fusion.
In the next section, we outline the problem of data fusion with particular focus on validity criteria that can be used to evaluate the quality of data fusion.
The main idea is applying Kriging interpolation method on cheap data points to estimate the aerodynamic coefficients' trends over the entire space of variables, and refining the trends with accurate sample points and data fusion.
This process can be divided into three levels: fusion diagnosis of data level, fusion diagnosis of feature level and fusion diagnosis of decision level.
There are mainly two fusion rules of CSS: data fusion rule and decision fusion rule.
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