Decision Algorithm of Effectiveness Evaluation Based on Variable Precision Rough Fuzzy Sets

被引:0
|
作者
Dong, Chengxi [1 ]
Wu, Dewei [1 ]
He, Jing [1 ]
机构
[1] AF Engn Univ, Telecommun Engn Inst, Xian 710077, Peoples R China
关键词
Variable Precision Rough Fuzzy Sets(VPRFS); Effectiveness Evaluation; Decision rules; Ant Colony Algorithm;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An algorithm of effectiveness evaluation decision rules is proposed based on the Variable Precision Rough Fuzzy Sets (VPRFS) theory. Fuzzy membership functions are acquired automatically by using of similarity clustering method, which transforms the continuous attribute values into the fuzzy values. With the concepts of fuzzy similarity relations and fuzzy similarity classes, lower and upper approximations expressions of VPRFS are given. Also, Ant Colony Algorithm is introduced for attribute reduction, and decision rules of effectiveness evaluation are acquired. Finally, by one instance, the algorithm is applied to decision rules acquisition of satellite navigation system combat effectiveness evaluation, and the result shows that the algorithm can find more objective and effective decision rules from the evaluation data and is a good method in applications to effectiveness evaluation decision.
引用
收藏
页码:2447 / 2451
页数:5
相关论文
共 50 条
  • [21] New results on granular variable precision fuzzy rough sets based on fuzzy (co)implications
    Wang, Chun Yong
    Wan, Lijuan
    FUZZY SETS AND SYSTEMS, 2021, 423 : 149 - 169
  • [22] A Variable Precision Fuzzy Rough Set Approach to a Fuzzy-Rough Decision Table
    Jian, Li-rong
    Li, Ming-yang
    2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL MODELING, SIMULATION AND APPLIED MATHEMATICS (CMSAM 2016), 2016, : 236 - 240
  • [23] On Variable Precision Generalized Rough Sets and Incomplete Decision Tables
    Syau, Yu-Ru
    Liau, Churn-Jung
    Lin, En-Bing
    FUNDAMENTA INFORMATICAE, 2021, 179 (01) : 75 - 92
  • [24] Variable precision rough sets in analysis of inconsistent decision tables
    Mieszkowicz-Rolka, A
    Rolka, L
    NEURAL NETWORKS AND SOFT COMPUTING, 2003, : 304 - 309
  • [25] Covering-Based Variable Precision (I, T)-Fuzzy Rough Sets With Applications to Multiattribute Decision-Making
    Jiang, Haibo
    Zhan, Jianming
    Chen, Degang
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2019, 27 (08) : 1558 - 1572
  • [26] Coverage-Based Variable Precision (I, PSO)-Fuzzy Rough Sets with Applications to Emergency Decision-Making
    Yin, Ran
    Chen, Minge
    Wu, Jian
    Liu, Yu
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2025, 18 (01)
  • [27] Granular variable precision L-fuzzy rough sets based on residuated lattices
    Qiao, Junsheng
    Hu, Bao Qing
    FUZZY SETS AND SYSTEMS, 2018, 336 : 148 - 166
  • [28] Variable precision fuzzy rough sets based on overlap functions with application to tumor classification
    Zhang, Xiaohong
    Ou, Qiqi
    Wang, Jingqian
    INFORMATION SCIENCES, 2024, 666
  • [29] A new approach on covering fuzzy variable precision rough sets based on residuated lattice
    Van Thien Le
    Hu, Bao Qing
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2017, 33 (06) : 3181 - 3190
  • [30] Intelligent information retrieval based on the variable precision rough set model and fuzzy sets
    He, M
    Feng, BQ
    ROUGH SETS, FUZZY SETS, DATA MINING, AND GRANULAR COMPUTING, PT 2, PROCEEDINGS, 2005, 3642 : 184 - 192