2 |
Consistency-driven methodology to manage incomplete linguistic preference relation: A perspective based on personalized individual semantics
|
|
|
|
BASE
|
|
Show details
|
|
4 |
Sentiment Analysis using TF-IDF Weighting of UK MPs’ Tweets on Brexit
|
|
|
|
BASE
|
|
Show details
|
|
5 |
Proportional hesitant 2-tuple linguistic distance measurements and extended VIKOR method: Case study of evaluation and selection of green airport plans
|
|
|
|
BASE
|
|
Show details
|
|
6 |
A Fuzzy Approach to Sentiment Analysis at the Sentence Level
|
|
|
|
BASE
|
|
Show details
|
|
7 |
Fuzzy convolutional deep-learning model to estimate the operational risk capital using multi-source risk events
|
|
|
|
BASE
|
|
Show details
|
|
8 |
Type-1 OWA Operators in Aggregating Multiple Sources of Uncertain Information: Properties and Real-World Applications in Integrated Diagnosis.
|
|
|
|
BASE
|
|
Show details
|
|
9 |
Genetic Algorithm-Based Fuzzy Inference System for Describing Execution Tracing Quality
|
|
|
|
BASE
|
|
Show details
|
|
10 |
Consistency improvement with a feedback recommendation in personalized linguistic group decision making
|
|
|
|
BASE
|
|
Show details
|
|
12 |
Attitude Quantifier Based Possibility Distribution Generation Method for Hesitant Fuzzy Linguistic Group Decision Making
|
|
|
|
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. ; The possibility distribution-based approach is one of the powerful tools available to manage hesitant fuzzy linguistic term set (HFLTS) information. However, existing possibility distribution studies have not considered the experts’ satisfied preference for HFLTSs in the process of generating the possibility distribution. This paper aims at filling this research gap. To achieve this goal, a novel possibility distribution generation method based on the concept of linguistic quantifier is proposed. This is accomplished by defining a new attitude linguistic quantifier, which is supported with theoretical results to analyze the relationship between the proposed attitude linguistic quantifier with the original linguistic quantifier, attitude indices and the expected linguistic term. The new possibility distribution generation method is proved to be (1) more general than the two main existing approaches, which are particular cases for specific linguistic quantifiers; and (2) useful to implement the concept of soft majority in the resolution process of the decision making situation. Additionally, a new two stages feedback mechanism of attitude adjustment and assessment adjustment is devised to guarantee the convergence of the consensus reaching process. Finally, a framework of group decision making with HFLTSs information is presented and an illustrative example is conducted to verify the proposed method.
|
|
URL: https://doi.org/10.1016/j.ins.2020.01.026 https://dora.dmu.ac.uk/handle/2086/19043
|
|
BASE
|
|
Hide details
|
|
13 |
Multi-stage consistency optimization algorithm to decision-making with incomplete probabilistic linguistic preference relation
|
|
|
|
BASE
|
|
Show details
|
|
14 |
Revisiting Fuzzy and Linguistic Decision-Making: Scenarios and Challenges for Wiser Decisions in a Better Way
|
|
|
|
BASE
|
|
Show details
|
|
15 |
ArAutoSenti: Automatic annotation and new tendencies for sentiment classification of Arabic messages
|
|
|
|
BASE
|
|
Show details
|
|
16 |
Personalized individual semantics-based approach for large scale failure mode and effect analysis with incomplete preference information
|
|
|
|
BASE
|
|
Show details
|
|
17 |
Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts
|
|
|
|
BASE
|
|
Show details
|
|
18 |
Type-1 OWA operators in aggregating multiple sources of uncertain information : properties and real world applications
|
|
|
|
BASE
|
|
Show details
|
|
19 |
Dealing with incomplete information in linguistic group decision making by means of Interval Type‐2 Fuzzy Sets
|
|
|
|
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)
|
|
BASE
|
|
Show details
|
|
20 |
Stochastic logistic fuzzy maps for the construction of integrated multirates scenarios in the financing of infrastructure projects
|
|
|
|
BASE
|
|
Show details
|
|
|
|