39,476 research outputs found
An approach for uncertainty aggregation using generalised conjunction/disjunction aggregators
Decision Support Systems are often used in the area of system evaluation. The quality of the output of such a system is only as good as the quality of the data that is used as input. Uncertainty on data, if not taken into account, can lead to evaluation results that are not representative. In this paper, we propose a technique to extend Generalised Con- junction/Disjunction aggregators to deal with un- certainty in Decision Support Systems. We first de- fine the logic properties of uncertainty aggregation through reasoning on strict aggregators and after- wards extend this logic to partial aggregators
Using Fuzzy Linguistic Representations to Provide Explanatory Semantics for Data Warehouses
A data warehouse integrates large amounts of extracted and summarized data from multiple sources for direct querying and analysis. While it provides decision makers with easy access to such historical and aggregate data, the real meaning of the data has been ignored. For example, "whether a total sales amount 1,000 items indicates a good or bad sales performance" is still unclear. From the decision makers' point of view, the semantics rather than raw numbers which convey the meaning of the data is very important. In this paper, we explore the use of fuzzy technology to provide this semantics for the summarizations and aggregates developed in data warehousing systems. A three layered data warehouse semantic model, consisting of quantitative (numerical) summarization, qualitative (categorical) summarization, and quantifier summarization, is proposed for capturing and explicating the semantics of warehoused data. Based on the model, several algebraic operators are defined. We also extend the SQL language to allow for flexible queries against such enhanced data warehouses
Pythagorean fuzzy combinative distance-based assessment with pure linguistic information and its application to financial strategies of multi-national companies
This article addresses the issue of selecting Financial Strategies in
Multi-National companies (F.S.M.). The F.S.M. typically has to consider
multiple factors involving multiple stakeholders and, hence,
can be handled by applying an appropriate Multi-Criteria Group
Decision-Making (M.C.G.D.M.) approach. To address this issue, we
develop an M.C.G.D.M. framework to tackle the F.S.M. problem. To
handle inherent uncertainty in business decisions as reflected by
linguistic reasoning, we embark on constructing a Linguistic
Pythagorean Fuzzy (L.P.F.) M.C.G.D.M. framework that is capable
of tackling both uncertain decision information and linguistic variables.
The proposed approach extends the combinative distancebased
assessment (C.O.D.A.S.) method into the L.P.F. environment,
and processes decision input expressed as Pythagorean fuzzy sets
(P.F.S.) and pure linguistic variables (rather than converting linguistic
information into fuzzy numbers). The developed L.P.F.-
C.O.D.A.S. technique aggregates the L.P.F. information and is
applied to the F.S.M. problem with uncertain linguistic information.
A comparative analysis is carried out to compare the results
obtained from the proposed L.P.F.-C.O.D.A.S. approach with those
from other extensions of C.O.D.A.S. Furthermore, a sensitivity analysis
is conducted to check the impact of changes in a distance
threshold parameter on the ranking results
The Interpretation-Construction Distinction in Patent Law
The ambiguity of claim language is generally considered to be the most important problem in patent law today. Linguistic ambiguity is believed to cause tremendous uncertainty about patent rights. Scholars and judges have accordingly devoted enormous attention to developing better linguistic tools to help courts understand patent claims.
In this article, we explain why this diagnosis is fundamentally wrong. Claims are not often ambiguous, and linguistic ambiguity is not a major cause of the uncertainty in patent law today. We shall explain what really causes the uncertainty in patent rights, how the erroneous diagnosis of linguistic ambiguity has led the literature off-track, and what will get us back on track to solving the uncertainty problem
The Encyclopedia of Neutrosophic Researchers - vol. 1
This is the first volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to the editor’s invitation. The authors are listed alphabetically. The introduction contains a short history of neutrosophics, together with links to the main papers and books. Neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic measure, neutrosophic precalculus, neutrosophic calculus and so on are gaining significant attention in solving many real life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and indeterminacy. In the past years the fields of neutrosophics have been extended and applied in various fields, such as: artificial intelligence, data mining, soft computing, decision making in incomplete / indeterminate / inconsistent information systems, image processing, computational modelling, robotics, medical diagnosis, biomedical engineering, investment problems, economic forecasting, social science, humanistic and practical achievements
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