SS-WCCI 2026

21-26 June 2026

Special Session on Information fusion techniques based on aggregation functions, preaggregation functions, and their generalizations

Maastricht Exhibition & Congress Center (MECC),
Maastricht, the Netherlands

Special Session

Information fusion techniques based on aggregation functions, preaggregation functions,
and their generalizations

SHORT DESCRIPTION: The search of new information fusion techniques under uncertainty is currently a hot topic in almost every research field, from image processing, classification, data stream clustering, brain computer interfaces, decision making to deep learning, transforms and adaptive neuro fuzzy inference systems. This interest has led to new analysis of the notion of aggregation function and the introduction of new concepts that go beyond usual aggregation functions, either by considering more general definitions (e.g., considering weaker forms of monotonicity), or by extending them to other frameworks different from that of the unit interval (e.g., intervals, lattices). The aim of this section is to promote the discussion of the up-to-date theoretical research in the topic, as well as their applications, in total connection with the interests of FUZZ-IEEE community, related to the theoretical and applied subjects covered by conference.

The special issue focuses on mathematical foundations, models and techniques for data fusion for Artificial Intelligence under uncertainty, aiming at disclosing the most recent and innovative developments in the field, including, but not limited to:

Theoretical results in aggregation functions, pre-aggregation functions, and fusion functions with other kinds of weaker monotonicity;
Theoretical results in common aggregation functions, pre-aggregation functions, and fusion functions on many-valued status (including, e.g., interval and lattice-valued);
Theoretical and applied results in the control of the uncertainty in interval-valued data fusion;
Fuzzy measures, fuzzy integrals, and their generalizations;
Other fusion functions, models, and techniques for data fusion under uncertainty;
(Adaptative) Neuro-fuzzy models and systems;
Deep (fuzzy) learning;
Fuzzy data stream;
Applications in decision making (including, e.g., multi-criteria decision making), image processing, classification and multi-label classification, machine learning, data stream clustering, and data flow prediction.