@inproceedings{966e8b0ac7ef4c3bb18be5e8ec7e7444,
title = "Rough fuzzy set model for set-valued ordered fuzzy decision system",
abstract = "The classical rough set theory can not be directly used to reduce knowledge in set-valued ordered fuzzy decision system. Firstly, we propose a dominance relation-based rough fuzzy set model in set-valued ordered fuzzy decision system, and some important properties are investigated. Then, based on rough fuzzy set, the definitions of approximation consistent set and assignment consistent set are given. Judgment theorems of approximation consistent set and assignment consistent set are also obtained, meanwhile, attribute reduction approach based on discernibility matrices is proposed to eliminate redundant attributes that are not essential from the view of fuzzy decisions. Finally, an example is given to illustrate the effectiveness of the proposed method.",
keywords = "Knowledge reduction, Rough fuzzy set, Set-valued ordered fuzzy decision system",
author = "Zhongkui Bao and Shanlin Yang and J. Zhao",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.; 9th International Conference on Rough Sets and Knowledge Technology, RSKT 2014 ; Conference date: 24-10-2014 Through 26-10-2014",
year = "2014",
doi = "10.1007/978-3-319-11740-9\_62",
language = "英语",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "673--682",
editor = "Duoqian Miao and Georg Peters and Qinghua Hu and Ruizhi Wang and Duoqian Miao and Georg Peters and Witold Pedrycz and Dominik {\'S}l{\c e}zak",
booktitle = "Rough Sets and Knowledge Technology - 9th International Conference, RSKT 2014, Proceedings",
}