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Development and Calibration of Route Choice Utility Models: Neuro-Fuzzy Approach.
- Source :
- Journal of Transportation Engineering; Mar/Apr2004, Vol. 130 Issue 2, p171-182, 12p, 5 Black and White Photographs, 3 Charts, 8 Graphs
- Publication Year :
- 2004
-
Abstract
- The neuro-fuzzy refers to the recent technology that couples the traditional fuzzy logic developments with neural nets training capabilities to compose the fuzzy logic’s knowledge base and fuzzy sets’ parameters optimally. This paper discusses the calibration methodology of a neuro-fuzzy logic for modeling the route choice behavior. The logic accounts for the various factors of potential effect on the route choice utility perceived by the traveler. The structure of the fuzzy control stages, the calibration of the membership functions, and the composition of the knowledge base are discussed in detail. Logic training is based on data extracted from a factorial experimental design model. The results of the fuzzy logic model are utilized for in-depth analyses of the travelers’ perceptions of the route utility in response to the various traffic states. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0733947X
- Volume :
- 130
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Journal of Transportation Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 12297884
- Full Text :
- https://doi.org/10.1061/(ASCE)0733-947X(2004)130:2(171)