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Experimental results on 21 non-linear regression datasets show that DGP-NF outperforms alternative models on 16 datasets and achieves competitive performance on the remaining ones, indicating generalization capability. The use of dynamic population and diversity control mechanisms proves effective in mitigating premature convergence and promoting broader exploration of the search space. Additionally, the proposed diversity-based pruning strategy demonstrates potential as a simple and effective approach for refining multi-gene individuals.<\/jats:p>","DOI":"10.1007\/s12065-026-01184-5","type":"journal-article","created":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T05:44:30Z","timestamp":1775108670000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Incremental evolutionary neuro-fuzzy system with dynamic population and diversity control"],"prefix":"10.1007","volume":"19","author":[{"given":"Glender","family":"Br\u00e1s","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fl\u00e1vio V. 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