2019 IEEE Symposium Series on Computational Intelligence

IEEE Symposium Series on Computational Intelligence

December 6-9, 2019 Xiamen, China


IEEE Symposium on Evolving and Autonomous Learning Systems (IEEE EALS)

The EALS 2019 Symposium will be a focal point for presentation of the recent advanced research results and industrial applications in the area of evolving and autonomously learning systems. The role of autonomous learning from (big) data (streams) is growing with the exponential explosion of amounts, complexity and hetero-genuous nature of the data we are living through. The traditional methods of machine learning, probabilistic and even computational intelligence techniques such as neural networks and fuzzy sets and systems require in practice a lot of handcrafting, make restrictive assumptions and are often not directly applicable to dynamically changing, evolving data with non-stationary properties, of hetero-genuous nature (mixing signals, image/video, text), categorical variables, etc. Extracting autonomously interpretable models which are not fixed, but dynamically evolving is a key challenges to be addressed. The Symposium has established track record and aims to keep and build upon this with the current event, EALS 2019.


New Adaptive and Evolving Learning Methods:

  • Evolving in Dynamic Environments
  • Drift and Shift in Data Streams
  • Self-monitoring Evolving Systems
  • Evolving Decision Systems / Evolving Perceptions
  • Self-organising Systems/ Evolving Neuro-fuzzy Systems
  • Neural Networks with Evolving Structure
  • Non-stationary Time Series Prediction with ES
  • Automatic Novelty Detection in Evolving Systems
  • Stability, Robustness, Unlearning Effects
  • Structure Flexibility and Robustness in Evolving Systems
  • Evolving Fuzzy Clustering Methods
  • Evolving Fuzzy Rule-based Classifiers
  • Evolving Intelligent Systems for Time Series Prediction
  • Evolving Intelligent System State Monitoring and Prognostics
  • Evolving Intelligent Controllers
  • Evolving Fuzzy Decision Support Systems
  • Evolving Consumer Behaviour Models

Real-world application:

  • Robotics and Control Systems
  • Industrial Applications
  • Data Mining and Knowledge Discovery
  • Intelligent Transport
  • Bio-Informatics
  • Defence

Symposium Chairs

Plamen Angelov

Lancaster University, UK



Dimitar Filev

Ford Motor Company, USA



Nikola Kasabov

Auckland University of Technology, New Zealand



Program Committee

Rashmi Dutta Baruah IIT, India
Abdelhamid Bouchachia University of Bournemouth, UK
Bruno Sielly Jales Costa IFRN, Brazil
Richard Duro niversity of La Coruna, Spain
Fernando Gomide University of Campinas, Brazil
Xiaowei Gu Lancaster University, UK
Lazaros Iliadis Aristotle University of Thessaloniki, Greece
Jose Antonio Iglesias University Carlos III, Spain
Janusz Kacprzyk Polish Academy of Sciences, Poland
Dmitry Kangin University of Exeter, UK
Edwin Lughofer University of Linz, Austria
Moamar Sayed-Mouchaweh University of Reims, France
Radu-Emil Precup Polytechnic Univ. of Timisoara, Romania
Witold Pedrycz University of Alberta, Canada
Araceli Sanchis University Carlos III, Madrid
Igor Skrjanc University of Ljubljana, Slovenia
Dr Ginalber Sera Instituto Federal de EducaçãoCiência e Tecnologia do Maranhão (IFMA), São Luís
Eric Anquietil Institut National des Sciences Appliquées (INSA), Rennes
Hai-Jun Rong Xi'an Jiaotong University, China
Hamid R. hazhoosh University of Waterloo, Canada
Di Wang Khalifa University, UAE
Ronald Yager Iona College, NY
Xiaojun Zeng Manchester University, UK