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  1. Fuzzy Optimization and Decision Making
  2. Fuzzy Optimization and Decision Making : Volume 10
  3. Fuzzy Optimization and Decision Making : Volume 10, Issue 1, March 2011
  4. Bipolar aggregation using the Uninorms
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Fuzzy Optimization and Decision Making : Volume 16
Fuzzy Optimization and Decision Making : Volume 15
Fuzzy Optimization and Decision Making : Volume 14
Fuzzy Optimization and Decision Making : Volume 13
Fuzzy Optimization and Decision Making : Volume 12
Fuzzy Optimization and Decision Making : Volume 11
Fuzzy Optimization and Decision Making : Volume 10
Fuzzy Optimization and Decision Making : Volume 10, Issue 4, December 2011
Fuzzy Optimization and Decision Making : Volume 10, Issue 3, September 2011
Fuzzy Optimization and Decision Making : Volume 10, Issue 2, June 2011
Fuzzy Optimization and Decision Making : Volume 10, Issue 1, March 2011
Sensitivity and stability analysis in fuzzy data envelopment analysis
The use of possibility theory in the definition of fuzzy Pareto-optimality
Some discussions on uncertain measure
Extension principles for interval-valued intuitionistic fuzzy sets and algebraic operations
Bipolar aggregation using the Uninorms
Mean-risk model for uncertain portfolio selection
Fuzzy Optimization and Decision Making : Volume 9
Fuzzy Optimization and Decision Making : Volume 8
Fuzzy Optimization and Decision Making : Volume 7
Fuzzy Optimization and Decision Making : Volume 6
Fuzzy Optimization and Decision Making : Volume 5
Fuzzy Optimization and Decision Making : Volume 4
Fuzzy Optimization and Decision Making : Volume 3
Fuzzy Optimization and Decision Making : Volume 2
Fuzzy Optimization and Decision Making : Volume 1

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Bipolar aggregation using the Uninorms

Content Provider Springer Nature Link
Author Yager, Ronald R. Rybalov, Alexander
Copyright Year 2010
Abstract In bipolar aggregation the total score depends not just on previous score and the value of additional argument but on distribution of all other arguments as well. In addition the process of bipolar aggregation is not Markovian, i.e. aggregation is not associative. To model bipolar aggregation was introduced general $${R_{G}^\ast}$$ aggregation based on uninorms. By discarding associativity we built a variation of the uninorm using generating functions that can be applied as an intuitively appealing bipolar aggregation operator. This modified uninorm operator will allow us to control the aggregation depending on distribution of the arguments above and below the neutral element: the closer proportion of arguments below the neutral value to 1 or to 0 the closer bipolar aggregation is to some t-norm or t-conorm with desirable properties.
Starting Page 59
Ending Page 70
Page Count 12
File Format PDF
ISSN 15684539
Journal Fuzzy Optimization and Decision Making
Volume Number 10
Issue Number 1
e-ISSN 15732908
Language English
Publisher Springer US
Publisher Date 2010-12-25
Publisher Place Boston
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Bipolar Uninorm Fuzzy sets Decision making Operations Research/Decision Theory Calculus of Variations and Optimal Control; Optimization Probability Theory and Stochastic Processes Artificial Intelligence (incl. Robotics) Optimization Mathematical Logic and Foundations
Content Type Text
Resource Type Article
Subject Artificial Intelligence Logic Software
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