On the fundamental convergence in the (C) mean in problems of information fusion

Abstract

The Choquet integral can be regarded as one of aggregation operators being used in information fusion. In this study, we offer an interpretation of sequences of measurable functions and the Choquet integral in the framework of information fusion. Based on an efficiency measure space, we also define a new concept of a fundamental convergence in the (C ) mean of sequences of measurable functions and discuss its theoretical underpinnings along with related interpretation issues as well as deliver some new results. Furthermore, an application of this concept is discussed in the context of information fusion. More specifically, based on the theoretical investigations, this idea is applied to the determination of a measurable function being used in the Choquet integral.

Some Characterizations of the Choquet Integral with Respect to a Monotone Interval-Valued Set Function

“…Other researchers have studied various convergence problems on monotone set functions and, on sequences of measurable functions, as well as applications. For example, the convergence in the (C) mean [6], on decision-making problems [7,8], on the Choquet weak convergence [9], on the monotone expectation [10], and on the aggregation approach [11].…”