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In general, projection methods are iterative algorithms that use projections onto sets while relying on the general principle that when a family of (usually closed and convex) sets is present, then projections onto the given individual sets are easier to perform than projections onto other sets (intersections, image sets under some transformation, etc).
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Complete geometric characterization for both sets is presented.
A preliminary approach based on (sets of) partially ordered sets is presented.
In this paper, a new integrated design concept evaluation approach based on vague sets is presented.
In addition, a metric expressing the computational weight of input sets is presented.
In Table 6, a list of these sets is presented.
The chemical domain of the sets is presented in terms of chemical structure, complexity, and polarity.
Performance achieved by each algorithm on validation sets is presented in Table 4.
The distribution of each of these sets is presented in Table 1.
The hierarchy depth of three testing sets is presented in Table 7.
A summary of 208 data sets is presented in Table 2.
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