Fuzzy entity alignment via knowledge embedding with awareness of uncertainty measure

2021 ◽  
Author(s):  
Wen Jiang ◽  
Yuanna Liu ◽  
Xinyang Deng
Keyword(s):  
Uncertainty Measure

Level of Uncertainty Measure

2010 ◽  
Author(s):  
Marjolijn L. Antheunis ◽  
Patti M. Valkenburg ◽  
Jochen Peter
Keyword(s):  
Uncertainty Measure

Application of the bootstrap method to quantify uncertainty in seismic hazard estimates

1992 ◽  
Vol 82 (1) ◽  
pp. 104-119
Author(s):  
Michéle Lamarre ◽  
Brent Townshend ◽  
Haresh C. Shah
Keyword(s):  
Confidence Interval ◽  
Seismic Hazard ◽  
Statistical Method ◽  
Bootstrap Method ◽  
Earthquake Magnitude ◽  
Earthquake Catalog ◽  
Uncertainty Measure ◽  
Attenuation Models ◽  
The Bootstrap Method

Abstract This paper describes a methodology to assess the uncertainty in seismic hazard estimates at particular sites. A variant of the bootstrap statistical method is used to combine the uncertainty due to earthquake catalog incompleteness, earthquake magnitude, and recurrence and attenuation models used. The uncertainty measure is provided in the form of a confidence interval. Comparisons of this method applied to various sites in California with previous studies are used to confirm the validity of the method.

Variable Precision Rough Set Model Based on Covering Relation and Uncertainty Measure

2013 ◽  
Vol 694-697 ◽  
pp. 2856-2859
Author(s):  
Mei Yun Wang ◽  
Chao Wang ◽  
Da Zeng Tian
Keyword(s):  
Rough Set ◽  
Uncertainty Measure ◽  
Probabilistic Measure ◽  
Covering Relation ◽  
Practical Applications ◽  
Variable Precision ◽  
Model Based ◽  
Equivalent Relation ◽  
Proposed Model ◽  
Variable Precision Rough Set

The variable precision probabilistic rough set model is based on equivalent relation and probabilistic measure. However, the requirements of equivalent relation and probabilistic measure are too strict to satisfy in some practical applications. In order to solve the above problem, a variable precision rough set model based on covering relation and uncertainty measure is proposed. Moreover, the upper and lower approximation operators of the proposed model are given, while the properties of the operators are discussed.

scholarly journals A New Uncertainty Measure in Belief Entropy Framework

2018 ◽  
Vol 9 (11) ◽  
Author(s):  
Moise Digrais Mambe ◽  
Tchimou N’Takp´e ◽  
Nogbou Georges ◽  
Souleymane Oumtanaga
Keyword(s):  
Uncertainty Measure ◽  
Belief Entropy

Prediction of First-Order Vessel Responses with Applications to Decision Support Systems

2015 ◽  
Author(s):  
Ulrik D. Nielsen ◽  
Toshio Iseki
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Simple Approach ◽  
Full Scale ◽  
Uncertainty Measure ◽  
First Order ◽  
Future Developments ◽  
Vessel Response ◽  
Scale Data

The paper presents a practical and simple approach for making vessel response predictions. Features of the procedure include a) predictions which are scaled so to better agree with corresponding true, future values to be measured at the time the predictions apply at; and b) predictions that are assigned an uncertainty measure to reflect a level of confidence. The approach is tested with full-scale data and the obtained results/predictions agree well with measured values. Potentially, the procedure is therefore very useful in future developments of general decision support systems.

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