Estimation of relevance and fusion of data sources using belief function theory: application to bioprocess

In this paper, we present an application of the belief function theory for the classification of physiological states in a bioprocess. It also takes account of the relevance of the data sources. The notion of conflict is used to evaluate the relevance of each data source. Another measure of conflict, based on a distance, is also used, and provides globally, better results than the classical notion of conflict used in the Dempster rule of fusion. Experimental results are presented for a bioprocess and show that, with the use of relevance, the results of classification are better.