CHANGEOVER FROM DECISION TREE APPROACH TO FUZZY LOGIC APPROACH WITHIN HIGHWAY MANAGEMENT
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F17%3A00311635" target="_blank" >RIV/68407700:21260/17:00311635 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.14311/NNW.2017.27.008" target="_blank" >http://dx.doi.org/10.14311/NNW.2017.27.008</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/NNW.2017.27.008" target="_blank" >10.14311/NNW.2017.27.008</a>
Alternative languages
Result language
angličtina
Original language name
CHANGEOVER FROM DECISION TREE APPROACH TO FUZZY LOGIC APPROACH WITHIN HIGHWAY MANAGEMENT
Original language description
This paper deals with the changeover from the decision tree (bivalent logic) approach to the fuzzy logic approach to highway traffic control, particularly to variable speed limit displays. The usage of existing knowledge from decision tree control is one of the most suitable methods for identification of the new fuzzy model. However, such method introduces several difficulties. These difficulties are described and possible measures are proposed. Several fuzzy logic algorithms were developed and tested by a microsimulation model. The results are presented and the finest algorithm is recommended for testing on the Prague City Ring Road in real conditions. This paper provides a guidance for researchers and practitioners dealing with similar problem formulation.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20104 - Transport engineering
Result continuities
Project
<a href="/en/project/TA02030522" target="_blank" >TA02030522: Development of a new generation of RLTC and testing environment (SIRID)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Neural Network World
ISSN
1210-0552
e-ISSN
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Volume of the periodical
27
Issue of the periodical within the volume
04
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
16
Pages from-to
181-196
UT code for WoS article
000402020800001
EID of the result in the Scopus database
2-s2.0-85020164494