Abstract
In this chapter, a neural network model is presented for forecasting the average speed values at highway traffic detectors locations using the Fuzzy ARTMAP theory. The performance of the model is measured by the deviation between the speed values provided by the loop detectors and the predicted speed values. Different Fuzzy ARTMAP configuration cases are analysed in their training and testing phases. Some ad-hoc mechanisms added to the basic Fuzzy ARTMAP structure are also described to improve the entire model performance. The achieved results make this model suitable for being implemented on advanced traffic management systems (ATMS) and advanced traveller information system (ATIS).
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References
Adeli, H. and Hung, S. L., 1995. Machine Learning-Neural Networks, Genetic Algorithms, and Fuzzy Systems. Wiley, New York.
Adeli, H. and Hung, S. L., 1994. ”An adaptive conjugate gradient learning algorithm for efficient training of neural networks”. Applied Mathematics and Computation 62 (1), 81–100.
Carpenter, G. A. et al., 1992. ”Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps”. Neural Networks, IEEE Transactions on Volume 3, Issue 5, September, pp. 698–713.
Dharia, A. and Adeli, H., 2003. ”Neural network model for rapid forecasting of freeway link travel time”. Engineering Applications of Artificial Intelligence, Volume 16, Issues 7–8, October–December, pp. 607–613.
Park, D. and Rilett, L.R., 1999. ”Forecasting freeway link travel times with a multilayer feedforward neural network”. Computer-Aided Civil and Infrastructure Engineering 14 (5), 357–367.
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© 2008 Springer-Verlag Berlin Heidelberg
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Boto-Giralda, D., Antón-Rodríguez, M., Díaz-Pernas, F., Díez-Higuera, J. (2008). Neural Network Model Based on Fuzzy ARTMAP for Forecasting of Highway Traffic Data. In: Cetto, J.A., Ferrier, JL., Costa dias Pereira, J., Filipe, J. (eds) Informatics in Control Automation and Robotics. Lecture Notes Electrical Engineering, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79142-3_9
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DOI: https://doi.org/10.1007/978-3-540-79142-3_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-79141-6
Online ISBN: 978-3-540-79142-3
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