Results 31 to 40 of about 2,059,205 (180)
On a Class of Second-Order PDE&PDI Constrained Robust Modified Optimization Problems
Mathematics, 2021 In this paper, by using scalar multiple integral cost functionals and the notion of convexity associated with a multiple integral functional driven by an uncertain multi-time controlled second-order Lagrangian, we develop a new mathematical framework on ...
Savin Treanţă
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Quality Measures in Uncertain Data Management [PDF]
, 2007 Many applications deal with data that is uncertain. Some examples are applications dealing with sensor information, data integration applications and healthcare applications. Instead of these applications having to deal with the uncertainty, it should be
Keijzer, A. de, Keulen, M. van
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Decision Trees for Uncertain Data [PDF]
2009 IEEE 25th International Conference on Data Engineering, 2009 Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information. Value uncertainty arises in many applications during the data collection process. Example sources of uncertainty include measurement/quantization errors, data staleness, and multiple repeated ...
Tsang, S +4 more
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Analyses of Indexing Techniques on Uncertain Data With High Dimensionality
IEEE Access, 2020 Deploying a solution for handling critical decision-based problem efficiently requires the processing of high-dimensional data. Over the years, due to modern technological advancement, unprecedented volume of uncertain data is been captured and this has ...
Ma'aruf Mohammed Lawal +3 more
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Belief Hierarchical Clustering [PDF]
, 2014 In the data mining field many clustering methods have been proposed, yet standard versions do not take into account uncertain databases. This paper deals with a new approach to cluster uncertain data by using a hierarchical clustering defined within the ...
J. Schubert +6 more
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Indexing the Earth Mover's Distance Using Normal Distributions [PDF]
, 2011 Querying uncertain data sets (represented as probability distributions) presents many challenges due to the large amount of data involved and the difficulties comparing uncertainty between distributions.
Ruttenberg, Brian E., Singh, Ambuj K.
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Evidential-EM Algorithm Applied to Progressively Censored Observations [PDF]
, 2014 Evidential-EM (E2M) algorithm is an effective approach for computing maximum likelihood estimations under finite mixture models, especially when there is uncertain information about data.
A.P. Dempster +5 more
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GraphSoft Set and Neutrosophic Context-Based Assessment of Instructional Quality under Uncertainty in University Badminton Classes [PDF]
Neutrosophic Sets and SystemsThis study proposes the GraphSoft Set, an innovative extension of Soft Set theory, to evaluate teaching quality in university public badminton classes.
Xiaoshi Bo
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Computing Skylines Over Uncertain Data
SSRN Electronic Journal, 2022 The uncertain data in our work is when values along each dimension of a database may contain both exact and continuous range values.
Razali Yaakob +3 more
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A Self-Adaptive Process Mining Algorithm Based on Information Entropy to Deal With Uncertain Data
IEEE Access, 2019 Process mining is a technology to gain knowledge of the business process by using the event logs and achieve a model of the process, which contributes to the detection and improvement of the business process.
Weimin Li +5 more
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