Today I read a paper titled “A neural network and iterative optimization hybrid for Dempster-Shafer clustering”
The abstract is:
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.