Abstract
In this paper, a novel recognition system based on rough neural network is presented for the application of vehicle classification in wireless sensor network. The proposed system is evaluated using real-world signal datasets as well as two conventional methods. Compared with them, approach based on rough neural network achieves high performance improvement. Furthermore, the purposed system is extended for multi-channel sensor data fusion directly. Since the experiment results are attractive, an algorithm based on rough neural network is believed to have potential for applications of recognition and data fusion in wireless sensor networks.
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© 2006 Springer-Verlag Berlin Heidelberg
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Huang, Q., Xing, T., Liu, H.T. (2006). Vehicle Classification in Wireless Sensor Networks Based on Rough Neural Network. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_9
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DOI: https://doi.org/10.1007/11760191_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34482-7
Online ISBN: 978-3-540-34483-4
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