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Statements

Subject Item
n2:RIV%2F00216305%3A26110%2F02%3APU34055%21RIV11-MSM-26110___
rdf:type
skos:Concept n12:Vysledek
dcterms:description
Relations among different characteristics (e.g. coal dust concentrations and explicability index) of coal dust are complex, integrated, difficult to quantify and therefore relatively ill known. Conventional experimental records (usually tables, graphs) are not suitable for efficient uncertainty reasoning. A fuzzy knowledge base is a flexible framework for acquisition of vague, sparse and inconsistent knowledge. The fuzzy reasoning is to some extent equivalent to a conventional interpolation algorithm capable of interpolating among variously accurate non-equidistant points in a multi-dimensional space. The pooling of the experimental records, industrial observations and retrieved literature knowledge items represent a trade off between minimal modifi-cation of the original data and elimination of obvious inconsistencies among all sets of data. This is an ad hoc and time consuming process that requires highly qualified field experts and knowledge engineers. A sequence of several modifications is needed Relations among different characteristics (e.g. coal dust concentrations and explicability index) of coal dust are complex, integrated, difficult to quantify and therefore relatively ill known. Conventional experimental records (usually tables, graphs) are not suitable for efficient uncertainty reasoning. A fuzzy knowledge base is a flexible framework for acquisition of vague, sparse and inconsistent knowledge. The fuzzy reasoning is to some extent equivalent to a conventional interpolation algorithm capable of interpolating among variously accurate non-equidistant points in a multi-dimensional space. The pooling of the experimental records, industrial observations and retrieved literature knowledge items represent a trade off between minimal modifi-cation of the original data and elimination of obvious inconsistencies among all sets of data. This is an ad hoc and time consuming process that requires highly qualified field experts and knowledge engineers. A sequence of several modifications is needed
dcterms:title
A Fuzzy Pooling of Coal Dust Knowledge A Fuzzy Pooling of Coal Dust Knowledge
skos:prefLabel
A Fuzzy Pooling of Coal Dust Knowledge A Fuzzy Pooling of Coal Dust Knowledge
skos:notation
RIV/00216305:26110/02:PU34055!RIV11-MSM-26110___
n3:aktivita
n16:V n16:Z
n3:aktivity
V, Z(MSM 261100009)
n3:dodaniDat
n15:2011
n3:domaciTvurceVysledku
n4:6838472 n4:3679586
n3:druhVysledku
n6:D
n3:duvernostUdaju
n17:S
n3:entitaPredkladatele
n14:predkladatel
n3:idSjednocenehoVysledku
637010
n3:idVysledku
RIV/00216305:26110/02:PU34055
n3:jazykVysledku
n21:eng
n3:klicovaSlova
Coal Dust, Fuzzy Logic, Foüzzy Pooling, Knowledge
n3:klicoveSlovo
n10:Knowledge n10:Fuzzy%20Logic n10:Fo%C3%BCzzy%20Pooling n10:Coal%20Dust
n3:kontrolniKodProRIV
[BAB0065A7696]
n3:mistoKonaniAkce
Praha
n3:mistoVydani
Praha
n3:nazevZdroje
CHISA 2002
n3:obor
n11:JP
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:rokUplatneniVysledku
n15:2002
n3:tvurceVysledku
Dohnal, Mirko Krejčí, Aleš
n3:typAkce
n13:EUR
n3:zahajeniAkce
2002-08-25+02:00
n3:zamer
n18:MSM%20261100009
s:numberOfPages
9
n9:hasPublisher
Česká společnost chemického inženýrství
n7:isbn
80-86059-33-2
n19:organizacniJednotka
26110