The research of a kind of rough logic neural network

Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology

Volumn 29, Issue 3, 2007, Pages 611-615

  Zhang, Dong Bo ^a,b   Wang, Yao Nan ^a  

^a HUNAN UNIVERSITY   (China)

^b XIANGTAN UNIVERSITY   (China)

Author keywords

Fuzzy Logic Neural Network (FLNN); Rough logic; Rough Logic Neural Network(RLNN); Rough set

Indexed keywords

FUZZY LOGIC; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; NEURAL NETWORKS; PATTERN RECOGNITION; REMOTE SENSING;

CHONGQING AREA; CLASSIFICATION EXPERIMENT; FUZZY LOGIC NEURAL NETWORK (FLNN); LANDSAT TM REMOTE SENSING IMAGE; ROUGH LOGIC NEURAL NETWORK (RLNN); ROUGH NEURAL NETWORK; ROUGH SET;

ROUGH SET THEORY;

EID: 34247343718     PISSN: 10095896     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (16)

1. Pawlak Z. Rough set theory and its application to data analysis. Cybernetics and Systems, 1998, 29(9): 661-688.
2. Pawlak Z. Rough set theory for intelligent industrial applications. Intelligent Processing and Manufacturing of Materials, IPMM'99, Honolulu, 10-15 July, 1999, 1: 37-44.
3. Zhang Dong-bo, Wang Yao-nan, and Yi Ling-zhi. Rough neural network and its application to intelligent information processing. Control and Decision, 2005, 20(2): 121-126.
4. Banerjee M, Mitra S, and Pal S K. Rough fuzzy MLP: Knowledge encoding and classification. IEEE Trans, on Neural Networks, 1998, 9(6): 1203-1216.
5. Yu Chunyan, Wu Minghui, and Wu Ming. Combining rough set theory with neural network theory for pattern recognition. International Conference on Robotics, Intelligent Systems and Signal Processing, Changsha, 2003: 880-885.
6. Chen Shuangye and Yi Jikai. A fuzzy neural network based on rough sets and its applications to chemical production process. Info-tech and Info-net, 2001. Proceedings, Beijing Oct 29-Nov 1, 2001, 4: 405-410.
7. Wu Zhaocong. Research on remote sensing image classification using neural network based on rough sets. Info-tech and Info-net, 2001. Proceedings, Beijing Oct 29-Nov 1, 2001, 4: 279-284.
8. Pawlak Z. Rough Logic, Bulletin of the Polish Academy of Sciences, Technical Science, 1987, 35: 253-258.
9. Yao Hong-xing, Zhao Lin-du, and Sheng Zhaohan. Application of multi-grade fuzzy neural networks in fault diagnosis of large machinery. Journal of Southeast University (Natural Science Edition), 2001, 31(2): 59-63.
10. Dougherty J, Kohavi R, and Shami M. Supervised and unsupervised discretization of continuous features. Proceedings of 12th International Conference on Machine Learning, Morgan Kaufmann, 1995: 194-202.
11. Nguyen H S and Skowron A. Quantization of real-valuedattributes. Second International Joint Conference on Information Sciences, Wrightsville Beach, NC, 1995: 34-37.
12. Dubois D and Prade H. Rough-fuzzy sets and fuzzy-rough sets. International Journal of General Systems, 1990, 17(2-3): 191-209.
13. Sarkar M and Yegnanarayana B. Fuzzy-rough membership functions. 1998 IEEE International Conference on Systems, Man and Cybernetics, San Diego, CA, USA, Oct. 11-14, 1998, 2: 2028-2033.
14. Sarkar M and Yegnanarayana B. Rough-fuzzy membership functions. The 1998 IEEE International Conference on Fuzzy Systems Proceedings, Anchorage, AK USA, May 4-9, 1998, 1: 796-801.