A Note on "New Estimation Method for the Membership Values in Fuzzy Sets"
Summary :
Chen et al., have proposed a new estimation method for the membership values in fuzzy sets. The proposed scheme takes input from empirical/experimental data, which reflect the expert's knowledge on the relative degree of belonging of the members, and then searches for the best fit membership values of the element. Through the estimation of the practical case (Sect. 3 in [1]) the algorithm suggests to normalize the estimated membership values if there is any among them more than one and change some condition to guarantee its positiveness. In this paper, we show how to use the same imposed condition to guarantee that the estimated membership values will be within the unit interval without normalization.
- Publication
- IEICE TRANSACTIONS on Information Vol.E84-D No.5 pp.675-678
- Publication Date
- 2001/05/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- LETTER
- Category
- Biocybernetics, Neurocomputing
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Elsaid Mohamed ABDELRAHIM, Takashi YAHAGI, "A Note on "New Estimation Method for the Membership Values in Fuzzy Sets"" in IEICE TRANSACTIONS on Information,
vol. E84-D, no. 5, pp. 675-678, May 2001, doi: .
Abstract: Chen et al., have proposed a new estimation method for the membership values in fuzzy sets. The proposed scheme takes input from empirical/experimental data, which reflect the expert's knowledge on the relative degree of belonging of the members, and then searches for the best fit membership values of the element. Through the estimation of the practical case (Sect. 3 in [1]) the algorithm suggests to normalize the estimated membership values if there is any among them more than one and change some condition to guarantee its positiveness. In this paper, we show how to use the same imposed condition to guarantee that the estimated membership values will be within the unit interval without normalization.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_5_675/_p
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@ARTICLE{e84-d_5_675,
author={Elsaid Mohamed ABDELRAHIM, Takashi YAHAGI, },
journal={IEICE TRANSACTIONS on Information},
title={A Note on "New Estimation Method for the Membership Values in Fuzzy Sets"},
year={2001},
volume={E84-D},
number={5},
pages={675-678},
abstract={Chen et al., have proposed a new estimation method for the membership values in fuzzy sets. The proposed scheme takes input from empirical/experimental data, which reflect the expert's knowledge on the relative degree of belonging of the members, and then searches for the best fit membership values of the element. Through the estimation of the practical case (Sect. 3 in [1]) the algorithm suggests to normalize the estimated membership values if there is any among them more than one and change some condition to guarantee its positiveness. In this paper, we show how to use the same imposed condition to guarantee that the estimated membership values will be within the unit interval without normalization.},
keywords={},
doi={},
ISSN={},
month={May},}
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TY - JOUR
TI - A Note on "New Estimation Method for the Membership Values in Fuzzy Sets"
T2 - IEICE TRANSACTIONS on Information
SP - 675
EP - 678
AU - Elsaid Mohamed ABDELRAHIM
AU - Takashi YAHAGI
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2001
AB - Chen et al., have proposed a new estimation method for the membership values in fuzzy sets. The proposed scheme takes input from empirical/experimental data, which reflect the expert's knowledge on the relative degree of belonging of the members, and then searches for the best fit membership values of the element. Through the estimation of the practical case (Sect. 3 in [1]) the algorithm suggests to normalize the estimated membership values if there is any among them more than one and change some condition to guarantee its positiveness. In this paper, we show how to use the same imposed condition to guarantee that the estimated membership values will be within the unit interval without normalization.
ER -
English
