TY - GEN
T1 - Dynamic Computing Rough Approximations for Variable Granular Structure Lattice-Valued Decision Systems
AU - Yu, Jian Hang
AU - Chen, Ming Hao
AU - Zhang, Biao
AU - Xu, Wei Hua
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/11/7
Y1 - 2018/11/7
N2 - A lattice-valued decision information system has condition attributes consisting real-valued, set-valued, interval-valued, fuzzy-valued, intuitionistic fuzzy-valued attribute and so on. Meanwhile, the information granule structure of information system may vary over time when new information arrives and redundant data leaves. How to quickly update the approximations of a concept invariable granular structure system which caused by adding or deleting attributes? In this paper, we propose two dynamic obtaining rough approximations approach for inserting and removing attributes, respectively. The novel updating mechanism enables additional knowledge to be obtained from the alterant datasets without neglecting the prior knowledge. Furthermore, a case study is conducted toverify the feasibility and effectiveness of the dynamic computing approaches.
AB - A lattice-valued decision information system has condition attributes consisting real-valued, set-valued, interval-valued, fuzzy-valued, intuitionistic fuzzy-valued attribute and so on. Meanwhile, the information granule structure of information system may vary over time when new information arrives and redundant data leaves. How to quickly update the approximations of a concept invariable granular structure system which caused by adding or deleting attributes? In this paper, we propose two dynamic obtaining rough approximations approach for inserting and removing attributes, respectively. The novel updating mechanism enables additional knowledge to be obtained from the alterant datasets without neglecting the prior knowledge. Furthermore, a case study is conducted toverify the feasibility and effectiveness of the dynamic computing approaches.
KW - Dynamic computing
KW - Lattice-valued decision information system
KW - Rough approximations
KW - Variable granular structure
UR - https://www.scopus.com/pages/publications/85058034382
U2 - 10.1109/ICMLC.2018.8526947
DO - 10.1109/ICMLC.2018.8526947
M3 - 会议稿件
AN - SCOPUS:85058034382
T3 - Proceedings - International Conference on Machine Learning and Cybernetics
SP - 25
EP - 30
BT - Proceedings of 2018 International Conference on Machine Learning and Cybernetics, ICMLC 2018
PB - IEEE Computer Society
T2 - 17th International Conference on Machine Learning and Cybernetics, ICMLC 2018
Y2 - 15 July 2018 through 18 July 2018
ER -