Chapter
Apr 26, 2012
WM Method and Its Application in Traffic Flow Modeling
Authors: Dewang Chen [email protected], Junping Zhang [email protected], and Shunping Jia [email protected]Author Affiliations
Publication: International Conference on Transportation Engineering 2007
Abstract
Extracting fuzzy rules automatically from data is a research direction of fuzzy system and data mining. The WM method is the one of the earliest algorithms. However, it only selects the rules which have the maximal degree, so it does not consider other conflicting rules. Two other methods are presented in this paper to select fuzzy rules, and one simulation data and one field traffic flow data are used to compare all three methods. The comparative results show that the weighted mean method has the best robustness and error-tolerance, which is more suitable for extracting rules from the real data with noise.
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Information & Authors
Information
Published In
International Conference on Transportation Engineering 2007
Pages: 346 - 351
Copyright
© 2007 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
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ASCE Technical Topics:
- Algorithms
- Artificial intelligence and machine learning
- Automation and robotics
- Computer programming
- Computing in civil engineering
- Data collection
- Engineering fundamentals
- Field tests
- Flow simulation
- Fuzzy logic
- Infrastructure
- Mathematics
- Methodology (by type)
- Models (by type)
- Research methods (by type)
- Systems engineering
- Tests (by type)
- Traffic engineering
- Traffic flow
- Traffic management
- Traffic models
- Transportation engineering
Authors
Affiliations
State Key Laboratory of Rail Traffic Control and Safety (Beijing Jiaotong University), China and School of Electronics and Information Engineering, Beijing Jiaotong University 100044, Beijing, China. E-mail: [email protected]
State Key Laboratory of Rail Traffic Control and Safety (Beijing Jiaotong University), China and Shanghai Key Lab of Intelligent Information Processing and Department of Computer Science and Engineering, Fudan University, 200433, Shanghai, China. E-mail: [email protected]
School of Traffic and Transportation, Beijing Jiaotong University, 100044, Beijing, China. E-mail: [email protected]
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