Interval-valued fuzzy graphs

Sunil Mathew, John N. Mordeson, Davender S. Malik

Research output: Chapter in Book/Report/Conference proceedingChapter

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 languageEnglish (US)
Title of host publicationStudies in Fuzziness and Soft Computing
PublisherSpringer Verlag
Pages231-269
Number of pages39
Volume363
DOIs
StatePublished - Jan 1 2018

Publication series

NameStudies in Fuzziness and Soft Computing
Volume363
ISSN (Print)1434-9922

Fingerprint

Fuzzy Graph
Interval-valued Fuzzy Set
Fuzzy sets
Interval
Fuzzy Sets
Fuzzy Control
Uncertainty
Fuzzy control

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Computational Mathematics

Cite this

Mathew, S., Mordeson, J. N., & Malik, D. S. (2018). Interval-valued fuzzy graphs. In 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.

Studies in Fuzziness and Soft Computing. Vol. 363 Springer Verlag, 2018. p. 231-269 (Studies in Fuzziness and Soft Computing; Vol. 363).

Research output: Chapter in Book/Report/Conference proceedingChapter

Mathew, S, Mordeson, JN & Malik, DS 2018, Interval-valued fuzzy graphs. in 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
Mathew S, Mordeson JN, Malik DS. Interval-valued fuzzy graphs. In Studies in Fuzziness and Soft Computing. Vol. 363. Springer Verlag. 2018. p. 231-269. (Studies in Fuzziness and Soft Computing). https://doi.org/10.1007/978-3-319-71407-3_7
Mathew, Sunil ; Mordeson, John N. ; Malik, Davender S. / Interval-valued fuzzy graphs. Studies in Fuzziness and Soft Computing. Vol. 363 Springer Verlag, 2018. pp. 231-269 (Studies in Fuzziness and Soft Computing).
@inbook{22ef5a9c250f4f6a80ab1279c9c2fa83,
title = "Interval-valued fuzzy graphs",
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.",
author = "Sunil Mathew and Mordeson, {John N.} and Malik, {Davender S.}",
year = "2018",
month = "1",
day = "1",
doi = "10.1007/978-3-319-71407-3_7",
language = "English (US)",
volume = "363",
series = "Studies in Fuzziness and Soft Computing",
publisher = "Springer Verlag",
pages = "231--269",
booktitle = "Studies in Fuzziness and Soft Computing",
address = "Germany",

}

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.

UR - http://www.scopus.com/inward/record.url?scp=85039989432&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85039989432&partnerID=8YFLogxK

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 -