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Most algorithms used to solve the matching problem can be categorized as either area-base techniques or feature-based techniques.
Existing methods concerning this problem can be categorized into two aspects, the centralized method and the decentralized method.
The approaches that have been proposed to address this problem can be categorized into three types: resampling methods, algorithmic adaptations and cost sensitive techniques.
Methodologies to solve this inverse problem can be categorized into iterative and direct methodologies, both having their inherent advantages and disadvantages.
In general, the research fields of localization for the LOS/NLOS mixture problem can be categorized into two parts: (1) the constrained least squares (LS) method using optimization such as the semidefinite relaxation and second-order cone relaxation [9 12] and (2) localization using robust statistics.
Many approaches to solving the IK problem can be categorized into (1) analytical-based and (2) learning-based methods.
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Nonlinear problems can be categorized according to several properties.
Many real-world problems can be categorized as constrained optimization problems.
The consensus problems can be categorized into two main groups: estimation consensus and detection consensus.
According to reports from organizations like the MNR (1994) and National Environment Management Authority (NEMA 2007), these problems can be categorized into land, water, forest, and biodiversity issues.
Multi-floor layout problem (MFLP) can be categorized as one of the most crucial basic problems in the real world especially in the field of plant layout design.
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