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008191104t20142014quca    ob   f000 0 eng d
040 |aCaOODSP|beng|erda|cCaOODSP
0410 |aeng|beng|bfre
0861 |aD68-4/224-2014E-PDF
1001 |aDoré, Pierre-Emmanuel, |eauthor.
24510|aModeling and combining information within belief functions theory in search and rescue applications / |cPierre-Emmanuel Doré, Irène Abi-Zeid, Anne-Laure Jousselme, Arnaud Martin, Patrick Maupin.
264 1|aQuebec (Quebec) : |bDefence Research and Development Canada - Valcartier, |c2014.
264 4|c©2014
300 |a1 online resource (ii, x, 50 pages, 2 unnumbered pages) : |billustrations (some colour).
336 |atext|btxt|2rdacontent
337 |acomputer|bc|2rdamedia
338 |aonline resource|bcr|2rdacarrier
4901 |aTechnical report ; |vDRDC Valcartier TR 2010-224
500 |a"April 2014."
504 |aIncludes bibliographical references (pages 37-38).
5203 |a"In this report, we study the expressiveness of the theory of belief functions in the particular case of Search And Rescue (SAR) operations. The theory of belief functions is a mathematical framework, which is used, as the probabilities, to represent the imperfections of a source of information. These imperfections are of different natures: reliability, vagueness, uncertainty, to name only a few. Representing and dealing with these imperfections in a SAR context is a major issue especially when one needs to combine and update information coming from heterogeneous and subjective sources. After having reminded some background results of the theory of optimal search, we have suggested some approaches of the SAR problem founded on the theory of belief functions"--Abstract, page i.
546 |aIncludes abstracts and summaries in English and French.
69207|2gccst|aRescue
69207|2gccst|aModels
7101 |aCanada. |bDefence R&D Canada.
7102 |aDefence R&D Canada - Valcartier.
830#0|aTechnical report (Defence R&D Canada)|vDRDC Valcartier TR 2010-224.|w(CaOODSP)9.820558
85640|qPDF|s1.77 MB|uhttps://publications.gc.ca/collections/collection_2019/rddc-drdc/D68-4-224-2014-eng.pdf