April 1, 2007 13:11 World Scientific Review Volume - 9in x 6in ipmu4 Chapter 1 A new hybrid fusion method for diagnostic systems A. Zemirline, L. Lecornu and B. Solaiman ITI Department ENST Bretagne 29285 Brest, France In this work, we present a new fusion method based on fuzzy set theory. This method consists of combining several data and knowledge bases of diagnostic systems. It is characterized by a hybrid fusion, which com- bines base fusion of data and knowledge of the Case-Based Reasoning diagnostic systems. The fusion method relies on a distortion measure of various diagnostic systems (of case and knowledge bases). This distor- tion measure is integrated into the diagnostic system in order to improve its performance. It is defined by confidence degrees associated to each parameter that contitutes the case and knowledge bases of diagnostic systems. The confidence degrees are then integrated into the diagnostic system procedure. 1.1. Introduction Nowadays, several institutions and organizations combine homogeneous data coming from different systems and/or produced at different instants. This situation is faced, in particular, by medical institutions, where a new set of data is to be stored regularly which is used, on the one hand, to ex- tract new information and, on the other hand, to update the older versions of data. There are three main types of fusion methods which can be distinguished according to the conceptual level of information: 1 data fusion, decision fusion and model fusion. • Data fusion is a fusion process operated on the first conceptual level of information. It consists of combining raw data resulting from several sources or various primitive levels extracted from only 1