Displaying similar documents to “Fuzzy sets and fusion of multisensor data”

Neuro-rough-fuzzy approach for regression modelling from missing data

Krzysztof Simiński (2012)

International Journal of Applied Mathematics and Computer Science

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Real life data sets often suffer from missing data. The neuro-rough-fuzzy systems proposed hitherto often cannot handle such situations. The paper presents a neuro-fuzzy system for data sets with missing values. The proposed solution is a complete neuro-fuzzy system. The system creates a rough fuzzy model from presented data (both full and with missing values) and is able to elaborate the answer for full and missing data examples. The paper also describes the dedicated clustering algorithm....

DFIS: A novel data filling approach for an incomplete soft set

Hongwu Qin, Xiuqin Ma, Tutut Herawan, Jasni Mohamad Zain (2012)

International Journal of Applied Mathematics and Computer Science

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The research on incomplete soft sets is an integral part of the research on soft sets and has been initiated recently. However, the existing approach for dealing with incomplete soft sets is only applicable to decision making and has low forecasting accuracy. In order to solve these problems, in this paper we propose a novel data filling approach for incomplete soft sets. The missing data are filled in terms of the association degree between the parameters when a stronger association...

On the comparison of some fuzzy clustering methods for privacy preserving data mining: Towards the development of specific information loss measures

Vicenç Torra, Yasunori Endo, Sadaaki Miyamoto (2009)

Kybernetika

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Policy makers and researchers require raw data collected from agencies and companies for their analysis. Nevertheless, any transmission of data to third parties should satisfy some privacy requirements in order to avoid the disclosure of sensitive information. The areas of privacy preserving data mining and statistical disclosure control develop mechanisms for ensuring data privacy. Masking methods are one of such mechanisms. With them, third parties can do computations with a limited...

Fuzzy approach for data association in image tracking.

Julio García, José Manuel Molina, Juan Alberto Besada, Javier I. Portillo (2003)

Mathware and Soft Computing

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A fuzzy system has been developed to ponder update decisions both for the trajectories and shapes estimated for targets. It is embedded in an A-SMGCS Surveillance function for airport surface, based on video data processing, in charge of the automatic detection, identification and tracking of all interesting targets (aircraft and relevant ground vehicles). The tracking system captures a sequence of images, preprocesses them to extract the moving regions (blobs), and associates the blobs...

Fuzzy clustering: Insights and new approach.

Frank Klawonn (2004)

Mathware and Soft Computing

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Fuzzy clustering extends crisp clustering in the sense that objects can belong to various clusters with different membership degrees at the same time, whereas crisp or deterministic clustering assigns each object to a unique cluster. The standard approach to fuzzy clustering introduces the so-called fuzzifier which controls how much clusters may overlap. In this paper we illustrate, how this fuzzifier can help to reduce the number of undesired local minima of the objective function that...

An approach to fuzzy temporal reasoning in medicine.

R. Marín, S. Barro, F. Palacios, R. Ruiz, F. Martín (1994)

Mathware and Soft Computing

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In this work we propose an approach for the application of a fuzzy temporal constraint model to intelligent patient monitoring tasks. After analyzing the requirements of the domain, we describe the approach that was followed in order to represent temporal information and solve queries on temporal relations. These processes require the cooperation of a temporal specialist with the domain reasoning mechanisms. The integration solution presented here corresponds to a stage of the implementation...