Results 271 to 280 of about 82,469 (304)

Robust clustering of imprecise data

Chemometrics and Intelligent Laboratory Systems, 2014
Abstract Robust fuzzy clustering models for fuzzy data are proposed. In particular, using a “Partitioning Around Medoids” (PAM) approach, first a timid robustification of fuzzy clustering for a general class of fuzzy data is proposed. Successively, we propose three robust fuzzy clustering models based on, respectively, the so-called metric, noise and
D'Urso P., DE GIOVANNI, LIVIA
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Geographic metadata: data quality, uncertainty and imprecision

International Journal of Reasoning-based Intelligent Systems, 2011
The semantic geospatial web illustrates the use of geospatial semantics. The geospatial data are organised through catalogues containing metadata records, which can be queried in order to give access to related resources. Metadata, which refer to data describing data, include the quality of them where many values are fuzzy and/or uncertain.
Karima Akli-Astouati, Ratiba Guebaili, Aïcha Mokhtari   +2 more
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Computation with imprecise geospatial data

Computers, Environment and Urban Systems, 1998
Imprecision in spatial data arises from the granularity or resolution at which observations of phenomena are made, and from the limitations imposed by computational representations, processing and presentational media. Precision is an important component of spatial data quality, and a key to appropriate integration of collections of data sets. Previous
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Reasoning with Imprecise and Vague Data

1993
In this chapter, we will be looking at models of uncertain reasoning which allow for imprecision and vagueness in a natural way. They achieve this by the use of a set theoretic component in the model. We will revisit the Dempster-Shafer theory in order to discuss its handling of imprecision, and introduce fuzzy sets and possibility theory in connection
Paul Krause, Dominic Clark
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Interpretation of Imprecision in Medical Data

2009
Imprecision is an intrinsic part of all data types and even more so of medical data. In this paper, we revisit the definition of imprecision as well as closely related concepts of incompleteness, uncertainty, inaccuracy, and, in general, imperfection of data.
Mila Kwiatkowska, Peter Riben, Krzysztof Kielan   +2 more
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Fuzzy programming and imprecise data

Civil Engineering Systems, 1984
Abstract The parameters of mathematical programming models for many civil engineering problems can only be stated imprecisely and this leads to the formulation of fuzzy programs. Considerable progress has been made recently in the solution of such programs.
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Hierarchical Clustering of Imprecise Data

International Journal Of Data Mining And Emerging Technologies, 2012
Clustering is an important data mining technique that possesses immense applications in many research areas. However, majority of the clustering algorithms available are focused towards data sets that contain precise values. But there are situations in which one can come across data sets whose objects take values that are imprecise or fuzzy in nature ...
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Contributions to reasoning on imprecise data

2018
This thesis contains four contributions which advocate cautious statistical modelling and inference. They achieve it by taking sets of models into account, either directly or indirectly by looking at compatible data situations. Special care is taken to avoid assumptions which are technically convenient, but reduce the uncertainty involved in an ...
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Bagging of credal decision trees for imprecise classification

Expert Systems With Applications, 2020
CARLOS J Mantas, Javier G Castellano, Joaquin Abellan   +2 more
exaly  

Statistics with Imprecise Data

2009
María Ángeles Gil, Olgierd Hryniewicz
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