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This approach, based on the principles of data fusion, has been largely used to generate not only consensus models of the activity landscape but also in many documented applications of data fusion [28 30].
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Thus, while the results that we have presented provide a basis for the use of data fusion methods in principle, they do not provide a guide as to the effectiveness of any specific fusion method in practice.
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.
Methods section presents the whole-analysis flowchart of data fusion and prediction.
Alexander promoted the concept of "data fusion": using advanced techniques to fuse multiple sources of data to produce more timely, useful intelligence.
The databases were searched using the two types of data fusion: similarity fusion (SF) and group fusion (GF).
Furthermore, they did not address the issue of data fusion.
E agr is the energy consumption 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.
Advanced principles of information fusion, causality theory with Bayesian networks, and capability dependencies will be explored.
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