### Abstract

The results in this chapter are based mostly on the works in Akram (Inf Sci, 181:5548–5564, 2011) [5], Akram and Dudek (Comput Math Appl, 61(2):289–299, 2011) [14], Akram et al. (J Appl Math, 2013, 2013) [19], Akram et al. (Afr math, 2014) [23]. In 1975, Zadeh (Inf Sci, 8:199–249, 1975) [194] introduced the notion of interval-valued fuzzy sets as an extension of fuzzy sets (Zadeh, Inf Control, 8:338–353, 1965, [190]) in which the values of the memberships degrees are intervals in [0, 1] instead of elements in [0, 1]. Interval-valued fuzzy sets provide a more adequate description of uncertainty than traditional fuzzy sets in some cases. It can therefore be important to use interval-valued fuzzy sets in applications, e.g., in fuzzy control.

Original language | English (US) |
---|---|

Title of host publication | Studies in Fuzziness and Soft Computing |

Publisher | Springer Verlag |

Pages | 231-269 |

Number of pages | 39 |

Volume | 363 |

DOIs | |

State | Published - Jan 1 2018 |

### Publication series

Name | Studies in Fuzziness and Soft Computing |
---|---|

Volume | 363 |

ISSN (Print) | 1434-9922 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Computer Science (miscellaneous)
- Computational Mathematics

### Cite this

*Studies in Fuzziness and Soft Computing*(Vol. 363, pp. 231-269). (Studies in Fuzziness and Soft Computing; Vol. 363). Springer Verlag. https://doi.org/10.1007/978-3-319-71407-3_7

**Interval-valued fuzzy graphs.** / Mathew, Sunil; Mordeson, John N.; Malik, Davender S.

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

*Studies in Fuzziness and Soft Computing.*vol. 363, Studies in Fuzziness and Soft Computing, vol. 363, Springer Verlag, pp. 231-269. https://doi.org/10.1007/978-3-319-71407-3_7

}

TY - CHAP

T1 - Interval-valued fuzzy graphs

AU - Mathew, Sunil

AU - Mordeson, John N.

AU - Malik, Davender S.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - The results in this chapter are based mostly on the works in Akram (Inf Sci, 181:5548–5564, 2011) [5], Akram and Dudek (Comput Math Appl, 61(2):289–299, 2011) [14], Akram et al. (J Appl Math, 2013, 2013) [19], Akram et al. (Afr math, 2014) [23]. In 1975, Zadeh (Inf Sci, 8:199–249, 1975) [194] introduced the notion of interval-valued fuzzy sets as an extension of fuzzy sets (Zadeh, Inf Control, 8:338–353, 1965, [190]) in which the values of the memberships degrees are intervals in [0, 1] instead of elements in [0, 1]. Interval-valued fuzzy sets provide a more adequate description of uncertainty than traditional fuzzy sets in some cases. It can therefore be important to use interval-valued fuzzy sets in applications, e.g., in fuzzy control.

AB - The results in this chapter are based mostly on the works in Akram (Inf Sci, 181:5548–5564, 2011) [5], Akram and Dudek (Comput Math Appl, 61(2):289–299, 2011) [14], Akram et al. (J Appl Math, 2013, 2013) [19], Akram et al. (Afr math, 2014) [23]. In 1975, Zadeh (Inf Sci, 8:199–249, 1975) [194] introduced the notion of interval-valued fuzzy sets as an extension of fuzzy sets (Zadeh, Inf Control, 8:338–353, 1965, [190]) in which the values of the memberships degrees are intervals in [0, 1] instead of elements in [0, 1]. Interval-valued fuzzy sets provide a more adequate description of uncertainty than traditional fuzzy sets in some cases. It can therefore be important to use interval-valued fuzzy sets in applications, e.g., in fuzzy control.

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U2 - 10.1007/978-3-319-71407-3_7

DO - 10.1007/978-3-319-71407-3_7

M3 - Chapter

VL - 363

T3 - Studies in Fuzziness and Soft Computing

SP - 231

EP - 269

BT - Studies in Fuzziness and Soft Computing

PB - Springer Verlag

ER -