16217 8 89054 2 256220 document 89054 danielson19a.pdf application/pdf 411b0297896f7b90b8d028a598075124 MD5 126563 2019-12-10 06:45:57 https://pure.iiasa.ac.at/id/eprint/16217/1/danielson19a.pdf 16217 1 1 application/pdf text en public cc_by_nc_4

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/89054 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/89054 http://eprints.org/relation/ismediumThumbnailVersionOf https://pure.iiasa.ac.at/id/document/89054 89059 2 256231 document 89059 small.jpg image/png dc8729049a28f9f3a78c7f1e97592ad8 MD5 1806 2019-12-10 06:56:07 https://pure.iiasa.ac.at/id/eprint/16217/6/small.jpg 16217 6 6 image/png other Thumbnails conversion from text to thumbnail_small en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/89054 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/89054 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/89054 archive 353 disk0/00/01/62/17 2019-12-10 06:49:15 2021-08-27 17:32:28 2019-12-10 06:49:15 article show Danielson M. Ekenberg L. 7576 0000-0002-0665-1889 Larsson A. pub prog_risk In this paper, we discuss representation and evaluation in the DecideIT 3.0 decision tool which is based on a belief mass interpretation of the background information. The decision components are imprecise in terms of intervals and qualitative estimates and we emphasise how multiplicative and additive aggregations influence the resulting belief distribution over the expected values. 2019-07 published http://proceedings.mlr.press/v103/danielson19a.html 79 public Proceedings of Machine Learning Research 103 121-124 TRUE 2640-3498 FALSE no info:eu-repo/semantics/article