Areas of interest include, but are not limited to:

Basic Methologies

• Evolving Soft Computing Techniques
• Evolving Fuzzy Systems
• Evolving Rule-Based Classifiers
• Evolving Neuro-Fuzzy Systems
• Adaptive Evolving Neural Networks
• Adaptive Evolving Fuzzy Systems
• Online Genetic and Evolutionary Algorithms
• Data Stream Mining
• Incremental and Evolving Clustering Approaches
• Adaptive Control
• Adaptive Pattern Recognition
• Computational Intelligence in Control and Estimation
• Incremental and Evolving ML Classifiers
• Adaptive Statistical Techniques
• Evolving Decision Systems
• Big Data
• Advanced Concepts

Problems and Methodologies in Data Streams

• Stability, Robustness, Convergence in Evolving Systems
• Online Feature Selection and Dimension Reduction
• Online Active and Semi-supervised Learning
• Online Complexity Reduction
• Computational Aspects
• Interpretability Issues
• Incremental Adaptive Ensemble Methods
• Online 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, System Identification, and Control 

• 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