Displaying similar documents to “DFIS: A novel data filling approach for an incomplete soft set”

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....

Rough set-based dimensionality reduction for supervised and unsupervised learning

Qiang Shen, Alexios Chouchoulas (2001)

International Journal of Applied Mathematics and Computer Science

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The curse of dimensionality is a damning factor for numerous potentially powerful machine learning techniques. Widely approved and otherwise elegant methodologies used for a number of different tasks ranging from classification to function approximation exhibit relatively high computational complexity with respect to dimensionality. This limits severely the applicability of such techniques to real world problems. Rough set theory is a formal methodology that can be employed to reduce...

Flexible information retrieval: some research trends.

Gabriella Pasi (2002)

Mathware and Soft Computing

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In this paper some research trends in the field of Information Retrieval are presented. The focus is on the definition of flexible systems, i.e. systems that can represent and manage the vagueness and uncertainty which is characteristic of the process of information searching and retrieval. In this paper the application of soft computing techniques is considered, in particular fuzzy set theory.

Improving surface defect detection for quality assessment of car body panels.

Christian Döring, Andreas Eichhorn, Daniela Girimonte, Rudolf Kruse (2004)

Mathware and Soft Computing

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Surface quality analysis of exterior car body panels was still character ized by manual detection of local form deviations and subjective evaluation by experts. The approach presented in this paper is based on 3-D image processing A major step towards automated quality control of produced panels is the classification of the different kinds of surface form deviations. In previous studies we compared the performance of different soft computing techniques for the detection of surface defect...