Thematic track Fuzzy Data Analysis (FDA) Call for Papers

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Fernando Antonio Campos Gomide

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Feb 28, 2025, 2:31:02 PM2/28/25
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The EPIA Conference on Artificial Intelligence is a well-established European conference. The 24th edition of the EPIA conference will take place at the University of Algarve, Portugal, in October 2025.


Thematic track Fuzzy Data Analysis (FDA) Call for Papers

October 1-3, 2025, Faro, Portugal.
Webpage: https://epia2025.ualg.pt/

Important dates

Paper submission deadline: 

May 23, 2025 (AoE)

Notification of paper acceptance:

July 4, 2025

Camera-ready papers deadline:

July 14, 2025 (AoE)

Conference:

October 1-3, 2025 

Proceedings and presentation

  • Accept papers will be included in the conference proceedings as long as at least one author is registered in EPIA 2025 by the deadline of early bird registration.
  • EPIA 2025 proceedings are indexed in Thomson Reuters ISI Web of Science, Scopus, DBLP and Google Scholar.

Introduction

Fuzzy Data Analysis (FDA) tackles a fundamental challenge in Data Science: making sense of data that is inherently uncertain, imprecise, or ambiguous. By leveraging Fuzzy Set Theory and Fuzzy Logic, FDA provides a powerful framework for analyzing, processing, and extracting insights from data where traditional methods struggle-particularly in scenarios that defy crisp categorizations and exact values.
This track aims to foster discussions and disseminate cutting-edge research in FDA methodologies and applications. We welcome contributions that explore innovative approaches to handling heterogeneous, high-dimensional, noisy, or uncertain data in real-world settings.

Topics of interest

Topics of interest include, but are not limited to:

  • Fuzzy Clustering, Fuzzy Classification and Fuzzy Regression • Fuzzy Intelligent Decision-making
  • Fuzzy Logic in Deep Learning
  • Fuzzy Modeling for ExplainableAI (XAI)
  • Fuzzy Optimization in AI
  • Fuzzy Systems in Natural Language Processing
  • Hybrid Fuzzy-AI Systems
  • Interval-value Fuzzy Logic in AI
  • Methods to improve models’interpretability using fuzzy techniques • Neurocomputing,Fuzzy Neural Nets, and Deep Learning
  • Real-Time Decision Making with Fuzzy Systems
  • Type-2 Fuzzy Systems
  • Real-world applications

We invite researchers, practitioners, and industry experts to submit their latest findings, case studies, and theoretical advancements in Fuzzy Data Analysis.

Organizing committee

  • Susana Nascimento, Universidade Nova de Lisboa, Portugal
  • Gozde Ulutagay, Ege University,Turkey
  • João Paulo Carvalho, INESC-ID /Instituto Superior Técnico, Universidade de Lisboa, Portugal






 

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