Object–Parameter Approaches to Predicting Unknown Data in an Incomplete Fuzzy Soft Set Cover

.blurhash-client-img { display: none !important; }

Object–Parameter Approaches to Predicting Unknown Data in an Incomplete Fuzzy Soft Set

International Journal of Applied Mathematics and Computer Science

Volume 27 (2017): Issue 1 (March 2017)

By: Yaya Liu, Keyun Qin, Chang Rao and Mahamuda Alhaji Mahamadu

Open Access

|May 2017

Authors

Yaya Liu

yayaliu@my.swjtu.edu.cn

College of Mathematics Southwest Jiaotong University, Chengdu, China

Keyun Qin

qinkeyun@home.swjtu.edu.cn

College of Mathematics Southwest Jiaotong University, Chengdu, China

Chang Rao

alvis.c@hotmail.com

College of Information Science and Technology Southwest Jiaotong University, Chengdu, China

Mahamuda Alhaji Mahamadu

mamahamadu@yahoo.com

Council for Scientific and Industrial Research PO 132, Accra, Ghana

DOI: https://doi.org/10.1515/amcs-2017-0011 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X

Journal RSS Feed

Language: English

Page range: 157 - 167

Submitted on: Apr 22, 2016

Accepted on: Oct 15, 2016

Published on: May 4, 2017

Published by: University of Zielona Góra

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

fuzzy soft set,

incomplete fuzzy soft set,

object-parameter approach,

similarity measures

Related subjects:

Applied mathematics

© 2017 Yaya Liu, Keyun Qin, Chang Rao, Mahamuda Alhaji Mahamadu, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Previous article Volume 27 (2017): Issue 1 (March 2017)Next article