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  4. Soft Discretization in a Classification Model for Modeling Adaptive Route Choice with a Fuzzy ID3 Algorithm
 
research article

Soft Discretization in a Classification Model for Modeling Adaptive Route Choice with a Fuzzy ID3 Algorithm

Park, Kyounga
•
Bell, Michael G. H.
•
Kaparlas, Ioannis
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2008
Transportation Research Record

This study introduces a way to overcome the sensitivity of decision trees used for route choice behavior studies by using fuzzy logic while preserving the advantages of decision trees and the C4.5 algorithm, namely, comprehensibility and ease of application. Soft discretization of continuous values in fuzzy decision trees can provide a more robust classification. Also, the use of fuzzy logic makes it possible to accommodate qualitative attributes describing route characteristics. Apart from these features, fuzzy decision tree learning algorithms are also capable of assigning numeric values on decisions about the degree of certainty of each recommendation emanating from the fuzzy reasoning. This feature makes it possible to solve the multiple suggestion problem whereby the classic decision tree may suggest that more than one route is optimal. To investigate improvements resulting from the application of fuzzy decision tree learning algorithms, software for an adaptive route choice model using a fuzzy decision tree learning algorithm, fuzzy ID3, was developed and simulation experiments with the model were carried out. The comparison of results with the nonfuzzy adaptive route choice model indicates better predictive accuracy and more effective applicability for the fuzzy model in practice.

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Type
research article
DOI
10.3141/2076-03
Author(s)
Park, Kyounga
Bell, Michael G. H.
Kaparlas, Ioannis
Belzner, Heldrun
Date Issued

2008

Publisher

National Academy of Sciences

Published in
Transportation Research Record
Start page

20

End page

28

Subjects

Decision Trees

•

Guidance

•

ICL

Editorial or Peer reviewed

REVIEWED

Written at

OTHER

EPFL units
NEARCTIS
Available on Infoscience
November 16, 2010
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/57614
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