UIDK-means: A multi-dimensional uncertain measurement data clustering algorithm

In uncertain measurement data clustering methods for networked measurement and test information system, most methods assume the probability density function or probability distribution function of the measurement data is known, which is in contradiction with the issue that this information is rarely available. So in this paper, interval data combined with statistic information is used to express multi-dimensional uncertain measurement data reasonably, a new uncertain distance computing method is proposed to measure the similarity of different uncertain data. And a new uncertain multi-dimension data clustering algorithm-UIDK-means based on the interval data is proposed and applied to uncertain measurement data. Experiment results show that the uncertain clustering algorithm can obtain better clustering precision with low computing complexity.