József Mezei

31367547700

Publications - 4

On possibilistic correlation coefficient and ratio for fuzzy numbers

József Mezei István Harmati P. Várlaki Robert Fullér

Publication Name: Recent Researches in Artificial Intelligence Knowledge Engineering and Data Bases 10th Wseas International Conference on Artificial Intelligence Knowledge Engineering and Data Bases Aiked 11

Publication Date: 2011-06-17

Volume: Unknown

Issue: Unknown

Page Range: 263-268

Description:

In this paper we show some properties of possibilistic correlation coefficient and correlation ratio for marginal possibility distributions. We will show some examples for their computation from some joint possibility distributions.

Open Access: Yes

DOI: DOI not available

An improved index of interactivity for fuzzy numbers

József Mezei P. Várlaki Robert Fullér

Publication Name: Fuzzy Sets and Systems

Publication Date: 2011-02-16

Volume: 165

Issue: 1

Page Range: 50-60

Description:

In this paper we will introduce a new index of interactivity between marginal possibility distributions A and B of a joint possibility distribution C. The starting point of our approach is to equip each γ-level set of C with a uniform probability distribution, then the probabilistic correlation coefficient between its marginal probability distributions is interpreted as an index of interactivity between the γ-level sets of A and B. Then we define the index of interactivity between A and B as the weighted average of these indexes over the set of all membership grades. This new index of interactivity is meaningful for the whole family of joint possibility distributions. © 2010 Elsevier B.V. All rights reserved.

Open Access: Yes

DOI: 10.1016/j.fss.2010.06.001

Some examples of computing the possibilistic correlation coefficient from joint possibility distributions

József Mezei P. Várlaki Robert Fullér

Publication Name: Studies in Computational Intelligence

Publication Date: 2010-11-03

Volume: 313

Issue: Unknown

Page Range: 153-170

Description:

In this paper we will show some examples for computing the possibilistic correlation coefficient between marginal distributions of a joint possibility distribution. First we consider joint possibility distributions, (1-x-y), (1-x 2-y 2), and (1-x 2-y) on the set {(x,y)≡R2| x≥0,y≥0,x+y≤1}, then we will show (i) how the possibilistic correlation coefficient of two linear marginal possibility distributions changes from zero to -1/2, and from -1/2 to -3/5 by taking out bigger and bigger parts from the level sets of a their joint possibility distribution; (ii) how to compute the autocorrelation coefficient of fuzzy time series with linear fuzzy data. © 2010 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-15220-7_13

A correlation ratio for possibility distributions

József Mezei P. Várlaki Robert Fullér

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2010-07-29

Volume: 6178 LNAI

Issue: Unknown

Page Range: 178-187

Description:

Generalizing the probabilistic correlation ratio we will introduce a correlation ratio for marginal possibility distributions of joint possibility distributions. © 2010 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-14049-5_19