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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">JWA</journal-id><journal-title-group><journal-title>Journal of World Architecture</journal-title></journal-title-group><issn>2208-3480</issn><eissn>2208-3499</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/jwa.v8i2.6920</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Research and Application of Deep Learning Technology in Prefabricated Buildings</title><url>https://artdesignp.com/journal/JWA/8/2/10.26689/jwa.v8i2.6920</url><author>GuoRong</author><pub-date pub-type="publication-year"><year>2024</year></pub-date><volume>8</volume><issue>2</issue><history><date date-type="pub"><published-time>2024-05-20</published-time></date></history><abstract>Prefabricated buildings have become an important development trend in the field of modern architecture because of their high efficiency and environmental friendliness. Artificial intelligence and deep learning technology have been increasingly applied in prefabricated buildings. Deep learning technology provides comprehensive optimization of building design, construction, quality control, and cost and schedule management through the learning and analysis of large amounts of data. 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