16 lines
2.6 KiB
Properties
16 lines
2.6 KiB
Properties
#Properties file for afryca.consensusmodel.quesada2015
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Bundle-Vendor = Sinbad\u00B2
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Bundle-Name = Quesada2015
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afryca.consensusmodel.quesada2015.information = Paper: F.J. Quesada, I. Palomares, L. Mart\u00EDnez, Managing Experts Behavior in Large-Scale Consensus Reaching Processes with Uninorm Aggregation Operators. Applied Soft Computing, submitted\\n\\n This consensus model extends the one presented in Palomares et al. (FUZZ-IEEE 2014) by introducing an approach based on uninorm aggregation operators to manage the behavior of experts in the consensus process. Due to the full reinforcement property of uninorm operators, they allow to weight experts based not only on their behavior at the current round, but also on their previous behavior since the beginning of the discussion. Furthermore, this approach reinforces positively or negatively the weight of experts with a repeated good or bad behavior, respectively, in several consensus rounds.
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afryca.consensusmodel.quesada2015.mainfeature = Fuzzy preference relations\\nComputation of weights for experts\\nUninorm aggregation operators\\nFeedback mechanism
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afryca.consensusmodel.quesada2015.name = F. Quesada et al. (2015)
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afryca.consensusmodel.quesada2015.observations = \u0020
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afryca.consensusmodel.quesada2015.variable.mu.description = Consensus degree threshold
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afryca.consensusmodel.quesada2015.variable.max_rounds.description = Maximum number of discussion rounds allowed
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afryca.consensusmodel.quesada2015.variable.acceptability_threshold.description = Acceptability threshold
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afryca.consensusmodel.quesada2015.variable.alpha.description = Lower parameter of the linguistic quantifier used to weight experts based on their cooperation coefficient (its value may increase as the consensus process goes on)
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afryca.consensusmodel.quesada2015.variable.beta.description = Higher parameter of the linguistic quantifier used to weight experts based on their cooperation coefficient (its value may increase as the consensus process goes on)
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afryca.consensusmodel.quesada2015.variable.increment.description = Increment of alpha and beta parameters in the quantifier
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afryca.consensusmodel.quesada2015.variable.h_start.description = Consensus round from which the membership function parameters of the linguistic quantifier start increasing, thus becoming more strict with the meaning of cooperativeness
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afryca.consensusmodel.quesada2015.variable.eta.description = Controls the degree of penalization when computing the cooperation coefficient
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afryca.consensusmodel.quesada2015.variable.g.description = Neutral element of the uninorm operator used to weight experts based on their behavior |