Special sessions

Call for special sessions

Please submit proposals (up to 1 page) in MS Word or RTF format by email to the official email address of the conference ifsa-eusflat_2021@sipkes.sk

The proposal should include the following information:
  1. Title: Propose a title of the special session.
  2. Abstract: Introduce a brief abstract of no more than approximately 100 words that allows conference attendees to understand the topic and the focus of the special session.
  3. Organizers: Provide a list of organizers with their affiliations and contacts and confirm you agree that this information will appear on the conference web.

Important: IFSA-EUSFLAT Conference is open to any topics related to the fuzzy set theory from the theoretical as well as application point of view, other topics from the area of the computational intelligence, or topics from machine learning, computational linguistics, rough sets or quantum structures etc. are highly welcome and encouraged to build special sessions or even special tracks.

Deadline for the special session proposals: October 31, 2020

List of accepted sessions

SS1 - Decision Making Under Uncertainty and Fuzzy Optimization: Theory, Algorithms, and Applications
SS2 - Interval Uncertainty
SS3 - Fuzzy Implication Functions
SS4 - Soft Computing for Evolving Data Streams: Advances in Real-Time Pattern Recognition
SS5 - Data Management in IoT-based Smart Environments:
Leveraging Computational Intelligence for Decision Making (DaMISE’2021)
SS6 - Representing and Managing Uncertainty: different scenarios, different tools
SS7 - Mathematical Fuzzy Logic
SS8 - Fuzzy Methods in Statistics and Data Analysis
SS9 - Fuzzy Technologies for Web Intelligence and Internet of Things
SS10 - Modelling Vagueness in Natural Language
SS11 - Models and Proofs of Cluster Validation
SS12 - Fuzzy Modelling and Control of Dynamic Systems
SS13 - Explainable AI
SS14 - CI-4-SDG: Computational Intelligence to help reaching the Sustainable Development Goals
SS15 - Modeling Decisions in AI
SS16 - Mathematical Methods Towards Dealing with Uncertainty in Data Sciences
SS17 - Theoretical Aspects of Pre-Aggregation Functions and Generalized Forms of Monotonicity and Aggregation
SS18 - Applications of Pre-Aggregation Functions and Generalized Forms of Aggregation
SS19 - Deep Learning Under Uncertain and Imperfect Information