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Statements

Subject Item
n2:RIV%2F68407700%3A21260%2F04%3A06106545%21RIV%2F2005%2FMSM%2F212605%2FN
rdf:type
skos:Concept n17:Vysledek
dcterms:description
The main objective of this workshop is to provide an overview of methods that belong to the field of computational intelligence and their suitability for transportation planning and modeling. The following methods will be addressed by this workshop: Fuzzy Logic, Artificial Neural Networks, Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Genetic Algorithms. The basic principles of these methods will be described and their practical applications will be illustrated with examples. Often the methods of computational intelligence suffer criticism about their performance due to inappropriate use to problems that they are not meant to serve. This workshop will offer the strengths and weaknesses of each method and describe the appropriate problems for each. The workshop will focus mainly on applications to data analysis and data mining. The main objective of this workshop is to provide an overview of methods that belong to the field of computational intelligence and their suitability for transportation planning and modeling. The following methods will be addressed by this workshop: Fuzzy Logic, Artificial Neural Networks, Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Genetic Algorithms. The basic principles of these methods will be described and their practical applications will be illustrated with examples. Often the methods of computational intelligence suffer criticism about their performance due to inappropriate use to problems that they are not meant to serve. This workshop will offer the strengths and weaknesses of each method and describe the appropriate problems for each. The workshop will focus mainly on applications to data analysis and data mining. Hlavním cílem tohoto příspěvku je popsat metody umělé inteligence jejich hlavní výhody a nevýhody. Hlavní důraz byl kladen na jejich aplikace v dopravě. Jednalo se zejména o následující metody: fuzzy logika, umělé neuronové sítě, adaptivní neuro=fuzzy inferenční systém (ANFIS), a genetické algorimy.
dcterms:title
Computational Intelligence in Transportation Applications Computational Intelligence in Transportation Applications Umělá inteligence v dopravních aplikacích
skos:prefLabel
Computational Intelligence in Transportation Applications Computational Intelligence in Transportation Applications Umělá inteligence v dopravních aplikacích
skos:notation
RIV/68407700:21260/04:06106545!RIV/2005/MSM/212605/N
n3:aktivita
n10:Z
n3:aktivity
Z(MSM 210000023)
n3:dodaniDat
n11:2005
n3:domaciTvurceVysledku
n14:2580144
n3:druhVysledku
n18:A
n3:duvernostUdaju
n15:S
n3:entitaPredkladatele
n8:predkladatel
n3:idSjednocenehoVysledku
558458
n3:idVysledku
RIV/68407700:21260/04:06106545
n3:jazykVysledku
n16:eng
n3:klicovaSlova
artificial intelligence; fuzzy logic; soft computing; transportation applications
n3:klicoveSlovo
n4:artificial%20intelligence n4:transportation%20applications n4:soft%20computing n4:fuzzy%20logic
n3:kodPristupu
n13:L
n3:kontrolniKodProRIV
[47D6DF478A34]
n3:mistoVydani
Athens
n3:nosic
neuvedeno
n3:obor
n5:BC
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:rokUplatneniVysledku
n11:2004
n3:tvurceVysledku
Přibyl, Ondřej
n3:zamer
n9:MSM%20210000023
n6:organizacniJednotka
21260