Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Chaoyao Wen"'
Autor:
Yu Tian, Pengfei Guan, Chaoyao Wen, Manjia Lu, Tong Li, Lei Fan, Qinfeng Yang, Youjun Guan, Xinchang Kang, Yuhe Jiang, Chengyun Ning, Rumin Fu, Guoxin Tan, Lei Zhou
Publikováno v:
ACS Applied Materials & Interfaces. 14:54488-54499
Bioadhesives are widely used in a variety of medical settings due to their ease of use and efficient wound closure and repair. However, achieving both strong adhesion and removability/reusability is highly needed but challenging. Here, we reported an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1becc46974b8eb8376bd7bf80957a60
https://doi.org/10.1021/acsami.2c14103
https://doi.org/10.1021/acsami.2c14103
Publikováno v:
IEEE Transactions on Industrial Informatics. 17:8324-8334
This article proposes an improved incremental random vector functional-link network (RVFL) with a compact structure and presents its application to quality prediction of blast furnace (BF) ironmaking processes. Different from the original RVFL, the i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b443d338266b313104c814a6ed898351
https://doi.org/10.1109/tii.2021.3069869
https://doi.org/10.1109/tii.2021.3069869
Autor:
Chaoyao Wen, Ping Zhou
Publikováno v:
2022 34th Chinese Control and Decision Conference (CCDC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::714231e78743e0bf3414572f2cdf5d81
https://doi.org/10.1109/ccdc55256.2022.10033459
https://doi.org/10.1109/ccdc55256.2022.10033459
Publikováno v:
Neurocomputing. 365:1-9
Innumerable complex industrial processes, such as blast furnace (BF) ironmaking process, greatly rely on some well-performing quality models to realize prediction and control of product quality. This paper proposes an improved orthogonal incremental
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::418f018b473e30ad12cf1a80e626bdfe
https://doi.org/10.1016/j.neucom.2019.06.062
https://doi.org/10.1016/j.neucom.2019.06.062