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Abstract: Neural network technology has not been fully utilized in data mining. The reason is two-sided. First, most neural algorithms need long-term training, and could not perform incremental learning. Second, the knowledge learned by neural networks is concealed in a lage amount of connections. In this paper, we develop a neural network method to mine typhoon knowledge through overcoming those two obstacles. Experimental results show that our method could return considerable reward. (Update)
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BibTeX entry: (Update)
@misc{ knowledge-proceedings,
author = "Z.-H. Zhou, S. Chen, and Z. Chen",
title = "Mining typhoon knowledge with neural networks"
booktitle = "Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence, 1999, pp.325-326"
address = "Chicago, IL"
page = "325-326"
year = "1999",
url = "citeseer.ist.psu.edu/zhou99mining.html" }
Citations (may not include all citations):158 Adaptive Pattern Classification and Universal Recoding, I: P.. (context) - Grossberg - 1976
38 Advanced Methods in Neural Computing (context) - Wasserman - 1993
22 Using Neural Networks for Data Mining - Craven, Shavlik - 1997
2 Research of Field Theory based Adaptive Resonance Neural Net.. (context) - Zhou, Chen et al.
2 Programs for Machine Learning (context) - Quitdan - 1993
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