Abstract
The case retrieval model based on neural network is presented to enhance the efficiency and quality of retrieving case in the case-based reasoning system of the motorcycle intelligent design. In the retrieval model, the adaptive resonance theory neural network was used to dynamically cluster the cases in the case base to narrow the searching range. The back propagation neural network was applied to memory the index of cases to retrieve quickly the similar case from the narrowed case base. Thus the efficiency and quality of retrieving case are improved. Finally, an example of the plan selection of motorcycle general design was given. Its result was contrasted with that of case retrieval based on the nearest neighbor method to demonstrate the effectives of the case retrieval model. The research shows that it is practicable and effective using the adaptive resonance theory and BP neural network to modeling the reasoning mechanism.
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© 2009 Springer-Verlag Berlin Heidelberg
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Ma, F., He, Y., Li, S., Chen, Y., Liang, S. (2009). Research on Case Retrieval of Case-Based Reasoning of Motorcycle Intelligent Design. In: Wang, H., Shen, Y., Huang, T., Zeng, Z. (eds) The Sixth International Symposium on Neural Networks (ISNN 2009). Advances in Intelligent and Soft Computing, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01216-7_81
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DOI: https://doi.org/10.1007/978-3-642-01216-7_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01215-0
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