{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T10:32:23Z","timestamp":1776162743441,"version":"3.50.1"},"reference-count":77,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T00:00:00Z","timestamp":1737072000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computation"],"abstract":"<jats:p>This study presents a detailed analysis of various machine learning models for predicting the interfacial bond strength of fiber-reinforced polymer (FRP) concrete, including multiple linear regression, Multigene Genetic Programming (MGGP), an ensemble of regression trees, Gaussian Process Regression (GPR), Support Vector Regression (SVR), and neural networks. The evaluation was based on their predictive accuracy. The optimal model identified was the GPR ARD Exponential model, which achieved a mean absolute error (MAE) of 1.8953 MPa and a correlation coefficient (R) of 0.9658. An analysis of this optimal model highlighted the most influential variables affecting the bond strength. Additionally, the research identified several models with lower expression complexity and reduced accuracy, which may still be applicable in practical scenarios.<\/jats:p>","DOI":"10.3390\/computation13010017","type":"journal-article","created":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T10:27:58Z","timestamp":1737109678000},"page":"17","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Comparative Analysis of Machine Learning Models for Predicting Interfacial Bond Strength of Fiber-Reinforced Polymer-Concrete"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0740-2136","authenticated-orcid":false,"given":"Miljan","family":"Kova\u010devi\u0107","sequence":"first","affiliation":[{"name":"Faculty of Technical Sciences, University of Pristina, Knjaza Milosa 7, 38220 Kosovska Mitrovica, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9500-7285","authenticated-orcid":false,"given":"Marijana","family":"Hadzima-Nyarko","sequence":"additional","affiliation":[{"name":"Faculty of Civil Engineering and Architecture Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 3, 31000 Osijek, Croatia"}]},{"given":"Predrag","family":"Petronijevi\u0107","sequence":"additional","affiliation":[{"name":"Faculty of Civil Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, 11000 Belgrade, Serbia"}]},{"given":"Tatijana","family":"Vasiljevi\u0107","sequence":"additional","affiliation":[{"name":"Faculty of Technical Sciences, University of Pristina, Knjaza Milosa 7, 38220 Kosovska Mitrovica, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8623-447X","authenticated-orcid":false,"given":"Miroslav","family":"Radomirovi\u0107","sequence":"additional","affiliation":[{"name":"Faculty of Technical Sciences, University of Pristina, Knjaza Milosa 7, 38220 Kosovska Mitrovica, Serbia"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hadzima-Nyarko, M., \u010colak, S., Bulaji\u0107, B.\u0110., and Ademovi\u0107, N. 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