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Consistency-driven methodology to manage incomplete linguistic preference relation: A perspective based on personalized individual semantics
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Sentiment Analysis using TF-IDF Weighting of UK MPs’ Tweets on Brexit
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Proportional hesitant 2-tuple linguistic distance measurements and extended VIKOR method: Case study of evaluation and selection of green airport plans
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A Fuzzy Approach to Sentiment Analysis at the Sentence Level
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Fuzzy convolutional deep-learning model to estimate the operational risk capital using multi-source risk events
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Type-1 OWA Operators in Aggregating Multiple Sources of Uncertain Information: Properties and Real-World Applications in Integrated Diagnosis.
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Genetic Algorithm-Based Fuzzy Inference System for Describing Execution Tracing Quality
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Consistency improvement with a feedback recommendation in personalized linguistic group decision making
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Attitude Quantifier Based Possibility Distribution Generation Method for Hesitant Fuzzy Linguistic Group Decision Making
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Multi-stage consistency optimization algorithm to decision-making with incomplete probabilistic linguistic preference relation
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Revisiting Fuzzy and Linguistic Decision-Making: Scenarios and Challenges for Wiser Decisions in a Better Way
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ArAutoSenti: Automatic annotation and new tendencies for sentiment classification of Arabic messages
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Personalized individual semantics-based approach for large scale failure mode and effect analysis with incomplete preference information
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Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts
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Type-1 OWA operators in aggregating multiple sources of uncertain information : properties and real world applications
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Abstract:
The type-1 ordered weighted averaging (T1OWA) operator has demonstrated the capacity for directly aggregating multiple sources of linguistic information modelled by fuzzy sets rather than crisp values. Yager's OWA operators possess the properties of idempotence, monotonicity, compensativeness, and commutativity. This paper aims to address whether or not T1OWA operators possess these properties when the inputs and associated weights are fuzzy sets instead of crisp numbers. To this end, a partially ordered relation of fuzzy sets is defined based on the fuzzy maximum (join) and fuzzy minimum (meet) operators of fuzzy sets, and an alpha-equivalently-ordered relation of groups of fuzzy sets is proposed. Moreover, as the extension of orness and andness of an Yager's OWA operator, joinness and meetness of a T1OWA operator are formalised, respectively. Then, based on these concepts and the Representation Theorem of T1OWA operators, we prove that T1OWA operators hold the same properties as Yager's OWA operators possess, i.e.: idempotence, monotonicity, compensativeness, and commutativity. Various numerical examples and a case study of diabetes diagnosis are provided to validate the theoretical analyses of these properties in aggregating multiple sources of uncertain information and improving integrated diagnosis, respectively.
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Keyword:
Electronic computers. Computer science
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URL: https://strathprints.strath.ac.uk/73842/1/Zhou_etal_IEEE_TFS_2020_Type_1_OWA_operators_in_aggregating_multiple_sources.pdf https://doi.org/10.1109/TFUZZ.2020.2992909 https://strathprints.strath.ac.uk/73842/
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Dealing with incomplete information in linguistic group decision making by means of Interval Type‐2 Fuzzy Sets
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In: ISSN: 0884-8173 ; EISSN: 1098-111X ; International Journal of Intelligent Systems ; https://www.hal.inserm.fr/inserm-03026626 ; International Journal of Intelligent Systems, Wiley, 2019, 34 (6), pp.1261-1280. ⟨10.1002/int.22095⟩ (2019)
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Stochastic logistic fuzzy maps for the construction of integrated multirates scenarios in the financing of infrastructure projects
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A T1OWA Fuzzy Linguistic Aggregation Methodology for Searching Feature-based Opinions.
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