Information aggregation in intelligent systems: An application oriented approach
This paper offers a comprehensive study of information aggregation in intelligent systems prompted by common engineering interest. After a motivating introduction we consider aggregation functions and their fundamental properties as a basis for further development. Four main classes of aggregation functions are identified, and important subclasses are described and characterized as prototypes. For practical purposes, we outline two procedures to identify aggregation function that fits best to empirical data. Finally, we briefly recall some applications of aggregation functions in decision making, utility theory, fuzzy inference systems, multisensor data fusion, image processing, and their hardware implementation.
aggregation function decision making fuzzy inference system multisensor data fusion mean triangular norm uninorm image approximation