### 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.

Original language | English |
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Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |

Pages | 269-277 |

Number of pages | 9 |

Volume | 5908 LNAI |

DOIs | |

Publication status | Published - 2009 |

Event | 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2009 - Delhi Duration: 2009 Dec 15 → 2009 Dec 18 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 5908 LNAI |

ISSN (Print) | 03029743 |

ISSN (Electronic) | 16113349 |

### Other

Other | 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2009 |
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City | Delhi |

Period | 09/12/15 → 09/12/18 |

### Fingerprint

### Keywords

- Fuzzy Random Variable
- Fuzzy t-test
- Restructuring
- Rough Sets

### ASJC Scopus subject areas

- Computer Science(all)
- Theoretical Computer Science

### Cite this

*Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)*(Vol. 5908 LNAI, pp. 269-277). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5908 LNAI). https://doi.org/10.1007/978-3-642-10646-0_33

**A fuzzy random variable approach to restructuring of rough sets through statistical test.** / Watada, Junzo; Lin, Lee Chuan; Qiang, Minji; Lin, Pei Chun.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).*vol. 5908 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5908 LNAI, pp. 269-277, 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2009, Delhi, 09/12/15. https://doi.org/10.1007/978-3-642-10646-0_33

}

TY - GEN

T1 - A fuzzy random variable approach to restructuring of rough sets through statistical test

AU - Watada, Junzo

AU - Lin, Lee Chuan

AU - Qiang, Minji

AU - Lin, Pei Chun

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

KW - Fuzzy Random Variable

KW - Fuzzy t-test

KW - Restructuring

KW - Rough Sets

UR - http://www.scopus.com/inward/record.url?scp=76649132363&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=76649132363&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-10646-0_33

DO - 10.1007/978-3-642-10646-0_33

M3 - Conference contribution

SN - 3642106455

SN - 9783642106453

VL - 5908 LNAI

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 269

EP - 277

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -