@inproceedings{baa986f761b64fffb88ea0431cdd1f97,

title = "A fuzzy random variable approach to restructuring of rough sets through statistical test",

abstract = "Usually it is hard to classify the situation where randomness and fuzziness exist simultaneously. This paper presents a method based on fuzzy random variables and statistical t-test to restructure a rough set. The algorithms of rough set and statistical t-test are used to distinguish whether a subset can be classified in the object set or not. The expected-value-approach is also applied to calculate the fuzzy value with probability into a scalar value.",

keywords = "Fuzzy Random Variable, Fuzzy t-test, Restructuring, Rough Sets",

author = "Junzo Watada and Lin, {Lee Chuan} and Minji Qiang and Lin, {Pei Chun}",

year = "2009",

doi = "10.1007/978-3-642-10646-0_33",

language = "English",

isbn = "3642106455",

volume = "5908 LNAI",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "269--277",

booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

note = "12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2009 ; Conference date: 15-12-2009 Through 18-12-2009",

}