Fuzzy metric approach to aggregation of risk levels

Svetlana Asmuss; Pāvels Orlovs

doi:10.1007/978-3-030-16024-1_22

Fuzzy metric approach to aggregation of risk levels

Svetlana Asmuss^*
, Pāvels Orlovs

^*Šī darba korespondējošais autors

Zinātniskās darbības rezultāts: Nodaļa grāmatā/enciklopēdijā/konferences krājumā › Nodaļa grāmatā › Pētniecība › koleģiāli recenzēts

Kopsavilkums

In this paper we propose a special construction of a general aggregation operator. The construction allows to aggregate fuzzy sets taking into account the distance between elements of the universe. We consider the case when fuzzy sets to be aggregated represent the risk level evaluation by several experts. We describe how the proposed construction could be applied for risk level assessment in the case when a strong fuzzy metric is used to characterize the similarity of objects under evaluation.

Oriģinālvaloda	Angļu
Publikācijas avota nosaukums	Studies in Computational Intelligence
Publikācijas vieta	Cham
Izdevējs	Springer
Lapas	175-181
Lapu skaits	7
Sējums	819
ISBN (Drukātā versija)	9783030160234
DOIs	https://doi.org/10.1007/978-3-030-16024-1_22
Publikācijas statuss	Publicēts - 2020

Publikāciju sērijas

Nosaukums	Studies in Computational Intelligence
Sējums	819
ISSN (Drukātā versija)	1860-949X

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10.1007/978-3-030-16024-1_22

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abstract = "In this paper we propose a special construction of a general aggregation operator. The construction allows to aggregate fuzzy sets taking into account the distance between elements of the universe. We consider the case when fuzzy sets to be aggregated represent the risk level evaluation by several experts. We describe how the proposed construction could be applied for risk level assessment in the case when a strong fuzzy metric is used to characterize the similarity of objects under evaluation.",

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author = "Svetlana Asmuss and Pāvels Orlovs",

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Fuzzy metric approach to aggregation of risk levels. / Asmuss, Svetlana; Orlovs, Pāvels.
Studies in Computational Intelligence. Sēj. 819 Cham: Springer, 2020. lpp. 175-181 (Studies in Computational Intelligence; Sēj. 819).

Zinātniskās darbības rezultāts: Nodaļa grāmatā/enciklopēdijā/konferences krājumā › Nodaļa grāmatā › Pētniecība › koleģiāli recenzēts

TY - CHAP

T1 - Fuzzy metric approach to aggregation of risk levels

AU - Asmuss, Svetlana

AU - Orlovs, Pāvels

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2020.

PY - 2020

Y1 - 2020

N2 - In this paper we propose a special construction of a general aggregation operator. The construction allows to aggregate fuzzy sets taking into account the distance between elements of the universe. We consider the case when fuzzy sets to be aggregated represent the risk level evaluation by several experts. We describe how the proposed construction could be applied for risk level assessment in the case when a strong fuzzy metric is used to characterize the similarity of objects under evaluation.

AB - In this paper we propose a special construction of a general aggregation operator. The construction allows to aggregate fuzzy sets taking into account the distance between elements of the universe. We consider the case when fuzzy sets to be aggregated represent the risk level evaluation by several experts. We describe how the proposed construction could be applied for risk level assessment in the case when a strong fuzzy metric is used to characterize the similarity of objects under evaluation.

KW - Aggregation operator

KW - Fuzzy metric

KW - Risk level assessment

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UR - https://www.scopus.com/pages/publications/85066145124

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T3 - Studies in Computational Intelligence

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BT - Studies in Computational Intelligence

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CY - Cham

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Fuzzy metric approach to aggregation of risk levels

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