2Rajagopalan C, Baldev R, Kalyanasudaram P. A softcomputing framework for fault diagnosis. Information Sciences, 2000, 127 (3-4): 87-100.
3Pawlak Z. Rough sets and intelligent data analysis. Information Sciences, 2002, 147(1-4): 1-12.
4Pawlak Z. Rough classification. International Journal of Human-Computer Studies, 1999, 51(2): 369-383.
5Shen L X, Francis E H T, Qu L S, et al. Fault diagnosis using rough sets theory. Computers in Industry, 2000,430): 61-72.
6Chmielewski M R, Grzymala-Busse J W. Global discretization of continuous attributes as preprocessing for machine learning. International Journal of Approximate Reasoning, 1996, 15(4): 319-331.
7Khoo L P, Zhai L Y. A rough set approach to the treatment of continuous-valued attributes in multi-concept classification for mechanical diagnosis. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2001,15(3): 211-221.
8Beynon M J, Peel M J. Variable precision rough set theory and data discretisation: an application to corporate failure prediction. Omega, 2001, 29(6): 561-576.
9Susmaga R. Analyzing discretizations of continuous attributes given a monotonic discrimination function.Intelligent Data Analysis, 1997, 1 (1 -4): 157 - 179.
10Kortelainen J. Applying modifiers to knowledge acquisition. Information Sciences, 2001, 134(1-4): 39-51.
