{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T05:33:41Z","timestamp":1763444021199,"version":"3.33.0"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Science and Technology Project of China Tobacco Industry Company Ltd., \u201cResearch and Application of AutoML Platform for Tobacco Production\u201d","award":["2023ZN02"],"award-info":[{"award-number":["2023ZN02"]}]},{"DOI":"10.13039\/501100008656","name":"Yunnan Daguan Laboratory Foundation","doi-asserted-by":"publisher","award":["YNDG2023010T11"],"award-info":[{"award-number":["YNDG2023010T11"]}],"id":[{"id":"10.13039\/501100008656","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3529992","type":"journal-article","created":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T18:44:03Z","timestamp":1737053043000},"page":"13052-13069","source":"Crossref","is-referenced-by-count":1,"title":["An Interpretable Prediction Method for Tobacco Drying Process Based on CGTNN"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-2152-5051","authenticated-orcid":false,"given":"Wencai","family":"Wang","sequence":"first","affiliation":[{"name":"Kunming Cigarette Factory, Hongyun Honghe Tobacco (Group) Company Ltd., Kunming, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0047-7308","authenticated-orcid":false,"given":"Chen","family":"Yang","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenwei","family":"Niu","sequence":"additional","affiliation":[{"name":"Kunming Cigarette Factory, Hongyun Honghe Tobacco (Group) Company Ltd., Kunming, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sidi","family":"Lin","sequence":"additional","affiliation":[{"name":"Kunming Cigarette Factory, Hongyun Honghe Tobacco (Group) Company Ltd., Kunming, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Gao","sequence":"additional","affiliation":[{"name":"Kunming Cigarette Factory, Hongyun Honghe Tobacco (Group) Company Ltd., Kunming, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhe","family":"Cao","sequence":"additional","affiliation":[{"name":"Kunming Cigarette Factory, Hongyun Honghe Tobacco (Group) Company Ltd., Kunming, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianning","family":"Chen","sequence":"additional","affiliation":[{"name":"Kunming Cigarette Factory, Hongyun Honghe Tobacco (Group) Company Ltd., Kunming, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianzhong","family":"Li","sequence":"additional","affiliation":[{"name":"Kunming Cigarette Factory, Hongyun Honghe Tobacco (Group) Company Ltd., Kunming, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengkui","family":"Li","sequence":"additional","affiliation":[{"name":"Kunming Cigarette Factory, Hongyun Honghe Tobacco (Group) Company Ltd., Kunming, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"95","article-title":"Temperature and humidity control points in cigarette production","volume":"9","author":"Fan","year":"2010","journal-title":"Sci. Innov. Herald"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2735-4"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3390\/pr10122747"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3934\/mbe.2021127"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1080\/07373937.2019.1633662"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1142\/S1793545815500145"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.powtec.2019.01.050"},{"issue":"3","key":"ref8","first-page":"513","article-title":"A multivariate time series prediction algorithm based on self-evolution pre-training","volume":"45","author":"Wan","year":"2022","journal-title":"Comput. J."},{"key":"ref9","first-page":"93","article-title":"Control method for outlet moisture content of tobacco drying based on a fusion attention temporal convolutional network","volume":"56","author":"Liu","year":"2023","journal-title":"Tob. Sci. Technol."},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1080\/07373937.2021.1876722"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/fskd.2018.8687157"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/itaic54216.2022.9836664"},{"key":"ref13","first-page":"1","article-title":"Quality prediction for process manufacturing based on a fusion of temporal knowledge graphs and CNN-LSTM","volume":"2024","author":"Yin","year":"2024","journal-title":"Comput. Integr. Manuf. Syst."},{"key":"ref14","first-page":"1","article-title":"Multi-step process quality prediction method based on multi-channel CNN-BiGRU and temporal pattern attention mechanism","author":"Yin","year":"2023","journal-title":"Comput. Integr. Manuf. Syst."},{"key":"ref15","first-page":"1","article-title":"Research on the inspection method for gas ultrasonic flowmeters based on feature engineering and GA-BP neural networks","volume":"2024","author":"Jin","year":"2024","journal-title":"Acta Metrol."},{"issue":"14","key":"ref16","first-page":"5372","article-title":"Prediction of power outage trends in Chinas power grid based on spearmans correlation coefficient and system inertia","volume":"43","author":"Yu","year":"5372","journal-title":"Proc. CSEE"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ssci47803.2020.9308570"},{"key":"ref18","first-page":"85","article-title":"Research on data collection and preprocessing methods in intelligent manufacturing workshops","volume":"10","author":"Zheng","year":"2022","journal-title":"Manuf. Technol. Mach. Tool"},{"key":"ref19","first-page":"1","article-title":"Quality prediction algorithm for process manufacturing integrating TAM-LSTNet-CEEMDAN-RF error correction model","author":"Hou","year":"2024","journal-title":"Mech. Sci. Technol."},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2023.102219"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-79148-7"},{"key":"ref22","article-title":"Improving long-term streamflow prediction in a poorly gauged basin using geo-spatiotemporal mesoscale data and attention-based deep learning: A comparative study","volume":"615","author":"Smith","year":"2023","journal-title":"Water Resour. Res."},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10735"},{"key":"ref24","first-page":"219","article-title":"Research on the outlet moisture content of airflow drying based on six sigma","volume":"46","author":"Wang","year":"2017","journal-title":"Mech. Manuf. Autom."},{"volume-title":"Cigarette Process Specifications","year":"2016","key":"ref25"},{"key":"ref26","first-page":"4765","article-title":"A unified approach to interpreting model predictions","volume-title":"Proc. 31st Int. Conf. Neural Inf. Process. Syst.","author":"Lundberg"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1098\/rsta.2020.0209"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2022.08.011"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-63262-x"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119140"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3304669"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122666"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.oceaneng.2024.117726"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.02.010"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2023.102130"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3393472"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2023.119086"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/10843206.pdf?arnumber=10843206","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,25]],"date-time":"2025-01-25T05:23:25Z","timestamp":1737782605000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10843206\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3529992","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2025]]}}}