{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T22:25:55Z","timestamp":1780611955309,"version":"3.54.1"},"reference-count":26,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T00:00:00Z","timestamp":1643068800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/R51357X\/1"],"award-info":[{"award-number":["EP\/R51357X\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Intelligent Systems"],"published-print":{"date-parts":[[2022,6]]},"abstract":"<jats:sec><jats:label\/><jats:p>Mechanical design is one of the essential disciplines in engineering applications, while inspirations of design ideas highly depend on the ability and prior knowledge of engineers or designers. With the rapid development of machine learning (ML) techniques, artificial intelligence (AI)\u2010based design methods are promising tools for the design of advanced engineering systems. So far, there have been some studies of 2D patterns and structural designs based on ML techniques. However, a particular challenge remains in allowing complex 3D mechanical designs using ML techniques. Herein, a novel and experience\u2010free method to equip ML models with 3D design capabilities by combining a convolutional neuron network (CNN) with a deep convolutional generative adversarial network (DCGAN) is developed. The model directly receives 2D image\u2010based training data that define the complex 3D structures of a specific machine part. After the training process, an infinite number of new 3D designs can be generated by the proposed model, with their geometric and mechanical properties being accurately predicted at the same time. Moreover, the generated new designs can be fed back to expand the original input datasets for further ML model training and updating.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.202100186","type":"journal-article","created":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T05:45:01Z","timestamp":1643089501000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Novel Self\u2010Updating Design Method for Complex 3D Structures Using Combined Convolutional Neuron and Deep Convolutional Generative Adversarial Networks"],"prefix":"10.1002","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9163-0133","authenticated-orcid":false,"given":"Zewen","family":"Gu","sequence":"first","affiliation":[{"name":"Department of Engineering Engineering Building Lancaster University  Lancaster LA1 4YW UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2635-9188","authenticated-orcid":false,"given":"Xiaonan","family":"Hou","sequence":"additional","affiliation":[{"name":"Department of Engineering Engineering Building Lancaster University  Lancaster LA1 4YW UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed","family":"Saafi","sequence":"additional","affiliation":[{"name":"Department of Engineering Engineering Building Lancaster University  Lancaster LA1 4YW UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianqiao","family":"Ye","sequence":"additional","affiliation":[{"name":"Department of Engineering Engineering Building Lancaster University  Lancaster LA1 4YW UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,1,25]]},"reference":[{"key":"e_1_2_8_2_1","unstructured":"A. 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