{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T12:20:45Z","timestamp":1776082845139,"version":"3.50.1"},"reference-count":24,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3517752","type":"journal-article","created":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T19:28:05Z","timestamp":1734377285000},"page":"197300-197311","source":"Crossref","is-referenced-by-count":8,"title":["Small Sample-Oriented Prediction Method of Mechanical Properties for Hot Rolled Strip Steel Based on Model Independent Element Learning"],"prefix":"10.1109","volume":"12","author":[{"given":"Hongyi","family":"Wu","sequence":"first","affiliation":[{"name":"Institute of New Iron and Steel Materials, Ningbo Iron and Steel Company Ltd., Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Borui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of New Iron and Steel Materials, Ningbo Iron and Steel Company Ltd., Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8791-4214","authenticated-orcid":false,"given":"Zhiwei","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of New Iron and Steel Materials, Ningbo Iron and Steel Company Ltd., Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s12613-022-2536-y"},{"key":"ref2","article-title":"Research microstructure and property prediction and optimization technology of hot-rolled strip based on industrial big data","author":"Wu","year":"2018"},{"key":"ref3","article-title":"Prediction of heat treatment performance and intelligent optimization of process parameters of aluminum alloy sheet and strip","author":"Li","year":"2020"},{"issue":"6","key":"ref4","first-page":"2","article-title":"Prediction model of mechanical properties of hot rolled strip based on improved stacked self-encoder","volume":"44","author":"Song","year":"2020","journal-title":"Metall. Ind. Autom."},{"issue":"4","key":"ref5","first-page":"51","article-title":"Prediction of mechanical properties of hot-rolled strip under small sample conditions combining semi-supervised learning","volume":"47","author":"Liu","year":"2023","journal-title":"Metall. Autom."},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.120696"},{"key":"ref7","first-page":"3907","article-title":"OOD-MAML: meta-learning for few-shot out-of-distribution detection and classification","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Jeong"},{"issue":"8","key":"ref8","first-page":"93","article-title":"Research on small-sample model generalization performance optimization based on meta-learning and data enhancement","volume":"8","author":"Deng","year":"2024","journal-title":"Modern Inf. Technol."},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-06118-z"},{"issue":"6","key":"ref10","first-page":"59","article-title":"Recognition of radar additive composite jamming with small data size","volume":"43","author":"Kang","year":"2023","journal-title":"J. Hangzhou Dianzi Univ. (Natural Sci.)"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.compstruct.2019.111264"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.commatsci.2019.03.037"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3390\/buildings12010065"},{"issue":"3","key":"ref14","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1504\/IJMR.2021.117918","article-title":"A deep learning model for the accurate prediction of the microstructure performance of hot rolled steel","volume":"16","author":"Song","year":"2021","journal-title":"Int. J. Manuf. Res."},{"key":"ref15","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","author":"Finn"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2021.108765"},{"key":"ref17","first-page":"1","article-title":"Improving imbalanced industrial datasets to enhance the accuracy of mechanical property prediction and process optimization for strip steel","volume":"2","author":"Li","year":"2023","journal-title":"J. Intell. Manuf."},{"issue":"2","key":"ref18","doi-asserted-by":"crossref","first-page":"239","DOI":"10.3901\/JME.2021.02.239","article-title":"Ensemble learning model for mechanical performance prediction of strip and its reliability evaluation","volume":"57","author":"Li","year":"2021","journal-title":"J. Mech. Eng."},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP39728.2021.9413446"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s42243-022-00815-2"},{"issue":"1","key":"ref21","first-page":"86","article-title":"Progress and practice of digitalization of whole steelmaking-rolling process","volume":"47","author":"He","year":"2023","journal-title":"Metall. Autom."},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.ensm.2020.06.033"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2021.02.042"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2020.00178"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10380310\/10802899.pdf?arnumber=10802899","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T20:09:49Z","timestamp":1736971789000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10802899\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":24,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3517752","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}