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SS02

SS02: ITOMAD – Intelligent Techniques for Optimization, Modeling, and Anomaly Detection

Esteban Jove

University of A Coruña, Spain

Paulo Novais

University of Minho, Portugal

José Luis Calvo Rolle

University of A Coruña, Spain

Abstract

Regardless of the context, it is essential to tackle critical challenges due to various factors such as climate change, an aging population, and new industrial demands. These challenges include minimizing energy consumption and emissions, enhancing human quality of life, and meeting industrial improvement needs. Those involved in industry and academia cannot overlook these realities, as they will shape the future.

In this context, the industry, along with areas such as building management and assistive technologies, plays a crucial role in developing various emerging techniques to achieve the previously mentioned goals. While traditional methods have met current demands, there is a clear need for new advanced improvements in the future.

This session offers an exciting opportunity to present and discuss the latest theoretical advancements and practical applications in Optimization, Modeling, and Anomaly Detection using computational intelligence methodologies. This includes, among other topics, the following areas of focus:

  • Energy efficiency and optimization.
  • Control Techniques efficiency and optimization.
  • Traditional systems improvement.
  • Industrial control new techniques.
  • Modeling of complex systems.
  • Process optimization new techniques.
  • Fault Detection and Diagnosis.
  • Techniques to improve robustness against system failure.
  • Computational intelligence developments aimed at human beings.

Special Issue of Journal of Logic and Computation

A Special Issue has been agreed with the editorial board of the Journal of Logic and Computation (Q1 in Logic Category – JCR) to publish an improved extension of the most interesting papers submitted to this ITOMAD Session.

We estimate a period of 6-9 months for final acceptance after the congress is celebrated. The papers must satisfy the following conditions:

  • They should not have been published previously
  • The expanded and revised version needs an overall similarity score lower than 40% or individual similarity score lower than 10%
  • The final acceptance is the Editor-in-Chief’s decision
  • Papers must be presented in Journal template
  • The content of the contribution must be under the scope of ITOMAD – IWANN topics 

Organizers

Dr. Esteban Jove is an assistant professor in Systems Engineering and Automatics at the Department of Industrial Engineering of the University of A Coruña (UDC). His main research lines were initially focused on hybrid intelligent systems to model non-linear systems using artificial intelligence techniques combined with clustering methods. This proposal is successfully applied to predict a wide range of industrial and biological systems, among others. Then, his research continued with a new research line dealing with anomaly detection using one-class techniques and projectionist methods in industrial processes and cybersecurity systems.

Dr. Paulo Novais is a Full Professor of Computer Science at the Department of Informatics, the School of Engineering, the University of Minho (Portugal) and a researcher at the ALGORITMI Centre in which he is the leader of the research group ISLab – Synthetic Intelligence lab, and the coordinator of the research line Computer Science and Technology (CST). He is the coordinator of LASI (Intelligent Systems Associate Laboratory), director of the PhD Program in Informatics , and co-founder and deputy director of the Master in Law and Informatics program at the University of Minho. He started his career developing scientific research in the field of Intelligent Systems/Artificial Intelligence (AI), namely in Knowledge Representation and Reasoning, Machine Learning and Multi-Agent Systems. In recent years, his interest was absorbed by the different, yet closely related, concepts of Ambient Intelligence/Ambient Assisted Living, Conflict Resolution, Behavioural Analysis, Intelligent Tutors and the incorporation of AI methods and techniques in these fields. His main research aim is to make systems a little smarter, intelligent and also reliable.

Dr. José Luis Calvo Rolle is a full professor in Systems Engineering and Automatics at the Department of Industrial Engineering of the University of A Coruña (UDC). He is a permanent researcher at the Center for Research in Information and Communication Technologies (CITIC) of the UDC. He is the coordinator of the research group Cybernetics Science and Technology, recognized as a Group with Growth Potential (GPC) by the Xunta de Galicia, and director of the Environmental Radioactivity Laboratory of the UDC. His main lines of research focus on applying intelligent techniques to different fields. In the last decade, he has worked, especially in industrial applications in the fields of biomedicine and energy. He has also developed applications based on soft computing for decision-making systems and machine learning techniques for pattern recognition and anomaly detection. Currently, his research is focused on complex system modeling, digital twin development, fault and anomaly detection, and cybersecurity, in most cases, with the goal of system optimization and control.