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Open image in new window Fig. 1 Collaborative algorithm using consensus quality.
As a third example of safety sensing investigation, the research [15] proposes a collaborative algorithm based on energy detection and weighted combining (similar to a reputation system) to prevent malicious users.
We study the feasible conditions for a holarchy and propose a collaborative algorithm to analyze the feasibility and award contracts to holons without constructing the whole model of a holarchy.
'Others Users Versions' are the versions of multiple users who have given their ideas on the same individual, and finally, 'Collaborative Version' automatically integrates all versions of all users to create a collaborative version, which makes use of our proposed collaborative algorithm using consensus quality.
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This approach is based on collaborative algorithms for minimizing consumption of sensor energy.
The objectives of this paper are to propose models and develop collaborative algorithms to guide the holons to form a holarchy to coherently move toward the desired goal state ultimately.
Network-based prediction algorithms, such as collaborative filtering algorithm, 74 network-based inference, 75, 76 and neighbor-edges based and unbiased leverage algorithm (Nebula), the latter developed in our laboratory, 77 have been proposed for predictions of HLA peptide binding.
These representations feed a neighborhood-based collaborative filtering algorithm, which is detailed in the "Recommendation" section.
Second, the system clusters existing users and identifies users' neighbors based on the collaborative filtering algorithm.
They offer implementations for Linear Regression and Isotonic Regression, and one collaborative filtering algorithm using Alternating Least Squares.
For seeking an acceptable balance so as to determine the optimal controller parameters, a collaborative design algorithm is proposed.
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