Compositive information measure of a fuzzy set

In the present communication, a parametric (R, S)-norm information measure for the Pythagorean fuzzy set has been proposed with the proof of its validity. The monotonic behavior and maximality feature of the proposed information measure have been studied and presented. Further, an algorithm for solving the multicriteria decision-making problem with the help of the proposed information measure has been provided keeping in view of the different cases for weight criteria, when weights are unknown and other when weights are partially known. Numerical examples for each of the case have been successfully illustrated. Finally, the work has been concluded by providing the scope for future work.

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COMPOSITIVE INFORMATION MEASURE OF A FUZZY SET

Advances in Fuzzy Systems — Applications and Theory - Fuzzy Logic and Soft Computing ◽

10.1142/9789812830753_0040 ◽

1995 ◽

pp. 353-359

Author(s):

Carlo Bertoluzza ◽

Teofilo Brezmes ◽

Gloria Naval

Keyword(s):

Fuzzy Set ◽

Information Measure

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Is Psychology a Science or a Fuzzy Set?

Contemporary Psychology ◽

10.1037/017151 ◽

1978 ◽

Vol 23 (5) ◽

pp. 319-320

Author(s):

LEWIS WOLFGANG BRANDT

Keyword(s):

Fuzzy Set

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Methodology of ECG Interpretation in the Padova Program

Methods of Information in Medicine ◽

10.1055/s-0038-1634804 ◽

1990 ◽

Vol 29 (04) ◽

pp. 386-392 ◽

Cited By ~ 12

Author(s):

R. Degani ◽

G. Bortolan

Keyword(s):

Decision Making ◽

Medical School ◽

Fuzzy Set ◽

Medical Knowledge ◽

Main Aspect ◽

Measurement Evaluation ◽

Possibility Distributions ◽

Linguistic Decision Making ◽

The University ◽

Ecg Interpretation

AbstractThe main lines ofthe program designed for the interpretation of ECGs, developed in Padova by LADSEB-CNR with the cooperation of the Medical School of the University of Padova are described. In particular, the strategies used for (i) morphology recognition, (ii) measurement evaluation, and (iii) linguistic decision making are illustrated. The main aspect which discerns this program in comparison with other approaches to computerized electrocardiography is its ability of managing the imprecision in both the measurements and the medical knowledge through the use of fuzzy-set methodologies. So-called possibility distributions are used to represent ill-defined parameters as well as threshold limits for diagnostic criteria. In this way, smooth conclusions are derived when the evidence does not support a crisp decision. The influence of the CSE project on the evolution of the Padova program is illustrated.

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