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Despite needing considerably higher training time when compared to the other attempted models, it performs at the highest accuracy, with 0.48 root mean squared error (RMSE) and 99.72% Pearson coefficient for goodness of fit (<jats:italic>R<\/jats:italic>-squared). In contrast, the rigid regression method had the worst predictions with 4.92 RMSE and 37.29% <jats:italic>R<\/jats:italic>-squared. Also, random forest, boosting methods, and simple feed forward neural network can be considered as a middle accuracy model with faster training time than CFNN. The findings of this study not only advance modeling of superconductors but also pave the way for applications and further research on ML plug-and-play codes for superconducting studies including modeling of superconducting devices.<\/jats:p>","DOI":"10.1088\/2632-2153\/ad45b1","type":"journal-article","created":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T22:43:39Z","timestamp":1714517019000},"page":"025040","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":22,"title":["A comprehensive machine learning-based investigation for the index-value prediction of 2G HTS coated conductor tapes"],"prefix":"10.1088","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-8316-4336","authenticated-orcid":false,"given":"Shahin Alipour","family":"Bonab","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2011-8423","authenticated-orcid":true,"given":"Giacomo","family":"Russo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1845-4006","authenticated-orcid":true,"given":"Antonio","family":"Morandi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7691-3485","authenticated-orcid":true,"given":"Mohammad","family":"Yazdani-Asrami","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"266","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"mlstad45b1bib1","doi-asserted-by":"publisher","first-page":"6506","DOI":"10.1103\/PhysRevB.58.6506","article-title":"Superconductor disks and cylinders in an axial magnetic field. 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