» Special Sessions

Submission Guidelines

All submissions of the special sessions must follow ICABDE requirements, and also must be done via EasyChair. All accepted papers of special sessions will be published in the conference proceedings of the series “Lecture notes on Data Engineering and Communications Technologies” of the Springer Publisher.

Special Session SS-01: Advanced Intelligent Systems and Fuzzy Approaches

  • Assoc. Prof. Hai Van Pham, Hanoi University of Science and Technology
  • Prof. Philip Moore, Lanzhou University

Aims and Scope:

Data science along with intelligent Systems research is increasingly considering fuzzy methods which are important for artificial intelligence (AI) applied to both ‘Blue Skye’ research and applied research which includes an increasing focus on business intelligence. Viewed from an organisational perspective, big-data analytic solutions are significant in a heterogeneous research fields including sentiment analysis and affective computing.

The aim of this session is to present topical and innovative research utilising AI theories, Applied Soft Computing and AI applications in intelligent systems. This session provides a forum for engineers, researchers, and scientists to disseminate and exchange current concepts and results in a research context.

The session will seek original contributions in all relevant areas including (but not limited to) the following topics (but not limited to) the following subject and topic areas.

Topics of Interest:

  • Fuzzy logic methods including fuzzy sets, picture fuzzy sets, and applied fuzzy systems.
  • Fuzzy rule-based systems and applications.
  • Natural language processing including sentiment analysis using heterogeneous techniques which can include ontology-based modeling, semantics, linguistics, Kansei engineering, and hedge algebras.
  • Soft computing models including reasoning techniques and applications.
  • Intelligent applications, hybrid systems including intelligent knowledge-based systems, and intelligent decision-support systems.
  • Dynamic and adaptive models in applications including machine learning with evolutionary systems, nature inspired systems, and artificial neural networks.
  • Models to enable intelligent forecasting, monitoring, and prediction in research, and ‘real-world’ applications.

Instruction for Authors: HERE.

Download the call for papers of the special session HERE.