Topics
Topics include, but are not restricted to, the following:
Basic Methologies
- Evolving Soft Computing Techniques
- Evolving Fuzzy Systems
- Evolving Rule-Based Classifiers
- Evolving Neuro-Fuzzy Systems
- Adaptive Evolving Neural Networks
- On-line Genetic and Evolutionary Algorithms
- Data Stream Mining
- Incremental and Evolving Clustering Approaches
- Adaptive Pattern Recognition
- Incremental and Evolving ML Classifiers
- Adaptive Statistical Techniques
- Evolving Decision Systems
- Big Data
- Advanced Concepts
Drifts and Shifts in Data Streams
- Stability, Robustness, Convergence in Evolving Systems
- On-line Feature Selection and Dimension Reduction
- On-line Active and Semi-supervised Learning
- On-line Complexity Reduction
- Computational Aspects
- Interpretability Issues
- Incremental Adaptive Ensemble Methods
- On-line Bagging and Boosting
- Self-monitoring Evolving Systems
- Human-Machine Interaction Issues
- Hybrid Modeling
- Transfer Learning
- Reservoir Computing
- Real-world Applications
EIS for On-Line Modeling and System Identification
- EIS for Time Series Prediction
- EIS for Data Stream Mining and Adaptive Knowledge Discovery
- EIS in Robotics, Intelligent Transport and Advanced Manufacturing
- EIS in Advanced Communications and Multi-Media Applications
- EIS in Bioinformatics and Medicine
- EIS in Online Quality Control and Fault Diagnosis
- EIS in Condition Monitoring Systems
- EIS in Adaptive Evolving Controller Design
- EIS in User Activities Recognition
- EIS in Huge Database and Web Mining
- EIS in Visual Inspection and Image Classification
- EIS in Image Processing
- EIS in Cloud Computing
- EIS in Multiple Sensor Networks
- EIS in Query Systems and Social Networks
- EIS in Alternative Statistical and Machine Learning Approaches