Computer Science – Artificial Intelligence
Scientific paper
2003-05-16
in Proceedings of EuroFusion98 International Conference on Data Fusion (EF'98), M. Bedworth, J. O'Brien (Eds.), pp. 29-36, Gre
Computer Science
Artificial Intelligence
8 pages, 10 figures
Scientific paper
In this paper we extend an earlier result within Dempster-Shafer theory ["Fast Dempster-Shafer Clustering Using a Neural Network Structure," in Proc. Seventh Int. Conf. Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 98)] where a large number of pieces of evidence are clustered into subsets by a neural network structure. The clustering is done by minimizing a metaconflict function. Previously we developed a method based on iterative optimization. While the neural method had a much lower computation time than iterative optimization its average clustering performance was not as good. Here, we develop a hybrid of the two methods. We let the neural structure do the initial clustering in order to achieve a high computational performance. Its solution is fed as the initial state to the iterative optimization in order to improve the clustering performance.
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