Information granularity model for evolving context-based fuzzy system

- A new operational framework to compromise between interpretability and accuracy is proposed.
- The proposed Evolving Information Granule (EIG) increases the information granules (rules) by partitioning the output domain.
- The distinct output-contexts are adapted using a constraint which has the dynamic nature.
- The overfitting criterion is estimated online and approximated from the current and previous evolving stage.
- The results show that the proposed model achieves a reasonable accuracy with lower number of rules.