Reduced multivariate polynomial-based neural network for automated traffic incident detection

Neural Networks

Volumn 21, Issue 2-3, 2008, Pages 484-492

  Srinivasan, D ^a   Sharma, V ^a   Toh, K A ^b  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b Yonsei University   (South Korea)

Author keywords

Least square estimator; Reduced multivariate polynomial model; Singular value decomposition

Indexed keywords

MATHEMATICAL MODELS; NEURAL NETWORKS; PROBLEM SOLVING; SINGULAR VALUE DECOMPOSITION; TELECOMMUNICATION TRAFFIC;

REDUCED MULTIVARIATE POLYNOMIAL MODELS; TRAFFIC INCIDENT DETECTION;

POLYNOMIALS;

ALGORITHM; ARTICLE; CLASSIFIER; INCIDENCE; MULTIVARIATE ANALYSIS; NERVE CELL NETWORK; PRIORITY JOURNAL; TRAFFIC ACCIDENT; TRAINING;

ACCIDENTS, TRAFFIC; ARTIFICIAL INTELLIGENCE; HUMANS; INFORMATION STORAGE AND RETRIEVAL; LEAST-SQUARES ANALYSIS; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 40649118931     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2007.12.028     Document Type: Article

References (19)

1. Ahmed S.R., and Cook A.R. Application of time-series analysis techniques to freeway incident detection. Transportation Research Record 841 (1982) 19-21
2. Berthold M.R., and Diamond J. Constructive training of probabilistic neural networks. Neurocomputing (1998) 167-183
3. Browne R., Foo S., Huynh S., Abdulhai B., and Hall F. Comparison and analysis tool for automatic incident detection. Freeway operations, high-occupancy vehicle systems traffic signal systems, and regional transportation systems management 2005. Transportation Research Record 1925 (2005) 58-65
4. Cheu R.L., and Ritchie S.G. Automated detection of lane-blocking freeway incidents using artificial neural networks. Transportation Research 3C 6 (1995) 371-388
5. Dia H., and Rose G. Development and evaluation of neural network freeway incident detection models using field data. Transportation Research 5C 5 (1998) 313-331
6. Haykin S. Neural networks: A comprehensive foundation (1992), Prentice Hall, Eaglewood Cli.s, NJ
7. Kamijo S., Matsushita Y., Ikeuchi K., and Sakauchi M. Traffic monitoring and accident detection at intersections. IEEE Transactions on Intelligent Transportation Systems 1 2 (2000) 108-118
8. Lee S.J., and Ouyang C.J. A neuro-fuzzy system modelling with self-constructing rule generation and hybrid svd-based learning. IEEE Transactions on Fuzzy Systems 11 3 (2003)
9. Mahmassani H. S., Haas C., Zhou S. & Peterman J. (1998). Evaluation of incident detection methodologies. Centre for Transport Research. FHWA/TX_00/1795-1
10. Oh C., Oh J.-S., and Ritchie S.G. Real-time hazardous traffic condition warning system: framework and evaluation. IEEE Transactions on Intelligent Transportation Systems 6 3 (2005) 265-272
11. Payne H. J., Helfenbein E. D., & Knobel H. C. (1976). Development and testing of incident detection algorithms. Report no. FHWA-RD-76-20, Vol. 2 Federal Highway Administration
12. Specht D.F. Probabilistic neural networks and general regression neural networks. In: Chen C.H. (Ed). Fuzzy logic and neural network handbook (1996), McGraw-Hill, New York 3.1-3.44
13. Srinivasan D., Jin X., and Cheu R.L. Evaluation of adaptive Neural Network models for freeway incident detection. IEEE Transactions on Intelligent Transportation Systems 5 1 (2004) 1-11
14. Srinivasan, D., Sanyal, S., & Sharma, V. (2007). Freeway incident detection using hybrid fuzzy neural network. IET, Intelligent Transportation Systems (in press)
15. Srinivasn D., and Sharma V. A reduced multivariate polynomial based neural network model pattern classifier for freeway incident detection. IJCNN (2007)
16. Tang S., and Gao H. Traffic-incident detection-algorithm based on nonparametric regression. IEEE Transactions on Intelligent Transportation Systems 6 1 (2005) 38-42
17. Toh K.-A., Tran Q.-L., and Srinivasan D. Benchmarking a reduced multivariate polynomial pattern classifier. Pattern Analysis and Machine Intelligence, IEEE Transactions 26 6 (2004) 740-755
18. Toh, K. -A., & Yau, W. -Y. (2002). Multi-modal biometrics fusion: Beyond optimal weighting. Multi-modal biometrics fusion: Beyond optimal weighting. Control, automation, robotics and vision. ICARCV 2002. In 7th International Conference: Vol. 2 (pp. 788-792)
19. Toh K.-A., Yau W.-Y., and Jiang X. A reduced multivariate polynomial model for multimodal biometrics and classifiers fusion. Circuits and Systems for Video Technology, IEEE Transactions on 14 2 (2004) 224-233