A cellular-based evolutionary approach for the extraction of emerging patterns in massive data streams

•A cellular-based evolutionary fuzzy system for the extraction of emerging patterns in high-speed, massive data streams is proposed.•Smart triggering of the learning method which updates the model only when required.•A reinitialisation and filtering strategy for reducing the extraction of redundant patterns is also defined.•The quality of knowledge extracted outperforms state-of-the-art methods.•The proposed method is able to process batches of data up to 750,000 instances.