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The results from all three methods consistently highlighted the water-to-cement ratio, fiber content, loading direction, and cement content as the most influential factors affecting strength prediction. Additionally, a user-friendly Graphical User Interface (GUI) was developed for practical application. In conclusion, predictive equations derived from evolutionary programming, along with GUI incorporating diverse fiber types and loading directions, enhance the efficiency of 3D printing processes in construction.<\/jats:p>\n          <jats:p>\n            <jats:bold>Graphical abstract<\/jats:bold>\n          <\/jats:p>","DOI":"10.1007\/s41062-025-02057-z","type":"journal-article","created":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T11:15:44Z","timestamp":1748430944000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Comparative analysis of evolutionary computational methods for predicting mechanical properties of fiber-reinforced 3D printed concrete"],"prefix":"10.1007","volume":"10","author":[{"given":"Usama","family":"Asif","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,28]]},"reference":[{"key":"2057_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/J.MATDES.2024.113159","volume":"244","author":"Y Su","year":"2024","unstructured":"Su Y, Iyela PM, Zhu J, Chao X, Kang S, Long X (2024) A Voronoi-based gaussian smoothing algorithm for efficiently generating RVEs of multi-phase composites with graded aggregates and random pores. 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