Wyniki wyszukiwania - BazTech

1

Flexible resampling for fuzzy data

Grzegorzewski Przemyslaw, Hryniewicz Olgierd, Romaniuk Maciej

International Journal of Applied Mathematics and Computer Science

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2020

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Vol. 30, no. 2

281--297

EN

In this paper, a new methodology for simulating bootstrap samples of fuzzy numbers is proposed. Unlike the classical bootstrap, it allows enriching a resampling scheme with values from outside the initial sample. Although a secondary sample may contain results beyond members of the primary set, they are generated smartly so that the crucial characteristics of the original observations remain invariant. Two methods for generating bootstrap samples preserving the representation (i.e., the value and the ambiguity or the expected value and the width) of fuzzy numbers belonging to the primary sample are suggested and numerically examined with respect to other approaches and various statistical properties.

2

Development of a fuzzy-driven system for ovarian tumor diagnosis

Żywica P., Dyczkowski K., Wójtowicz A., Stachowiak A., Szubert S., Moszyński R.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 4

632--643

EN

In this paper we present OvaExpert, an intelligent system for ovarian tumor diagnosis. We give an overview of its features and main design assumptions. As a theoretical framework the system uses fuzzy set theory and other soft computing techniques. This makes it possible to handle uncertainty and incompleteness of the data, which is a unique feature of the developed system. The main advantage of OvaExpert is its modular architecture which allows seamless extension of system capabilities. Three diagnostic modules are described, along with examples. The first module is based on aggregation of existing prognostic models for ovarian tumor. The second presents the novel concept of an Interval-Valued Fuzzy Classifier which is able to operate under data incompleteness and uncertainty. The third approach draws from cardinality theory of fuzzy sets and IVFSs and leads to a bipolar result that supports or rejects certain diagnoses.

3

OvaExpert: an intelligent medical diagnosis support system for ovarian tumor

Żywica P., Apolinarski S., Kubiński B.

Journal of Medical Informatics & Technologies

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2015

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Vol. 24

183--190

EN

In this paper we present OvaExpert, an intelligent system for ovarian tumor diagnosis. We give an overview of its features and main design assumptions. As a theoretical framework the system uses fuzzy set theory and other soft computing techniques. This makes it possible to handle uncertainty and incompleteness of the data which is an unique feature of developed system. The main advantage of OvaExpert is its modular architecture which allows seamless extension of system capabilities. Two diagnostic modules are described in the paper along with examples. First module is based on aggregation of existing prognostic models for ovarian tumor. Second, on novel concept of Interval– Valued Fuzzy Classifier which is able to operate under data incompleteness and uncertainty.

4

Project management subject to imprecise activity network and cost estimation constraints

Pisz I., Banaszak Z.

Applied Computer Science

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2010

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Vol. 6, no 1

7--28

EN

The new approach to project planning assuming soft links between activities and imprecise cost of activities execution is considered. In that context, the method allowing one to estimate the duration and the cost of project execution is proposed. The illustrative example emphasizing the advantages of the approach proposed is enclosed.