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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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Abstract:
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. ; As a forward-looking reliability-management engineering technique, failure mode and effect analysis (FMEA) has been widely utilized to improve the reliability of products, processes, systems, and services. In practice, multiple responsible parties for FMEA implementation have different backgrounds, knowledge levels, and opinions. Integrating consensus into FMEA has some notable merits: the connections between FMEA participants can be strengthened, and a collective solution with a high degree of acceptability to the FMEA problem can be yielded. Meanwhile, the social network relationship among FMEA participants should be an essential element in FMEA because the participants’ opinions are subject to influence by each other and likely to evolve due to their social network interactions. Thus, this study first proposes a social network consensus model with minimum adjustment distance to assist FMEA participants in attaining a consensus, in which participants utilize a linguistic distribution assessment approach to represent their opinions. Second, an opinion evolution-based social network consensus model with minimum adjustment distance is further presented by considering the phenomenon of opinion evolution. Finally, some theoretical analyses, a case study, and a detailed comparative analysis are presented to verify the validity of the proposed FMEA approach.
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Keyword:
consensus; failure mode and effect analysis; opinion evolution; Reliability management; social network
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URL: https://dora.dmu.ac.uk/handle/2086/20598 https://doi.org/10.1016/j.ress.2020.107425
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18 |
Type-1 OWA operators in aggregating multiple sources of uncertain information : properties and real world applications
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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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