Vote for your favorite mineral in #MinCup25! - Silver vs. Baryte
Are you ready for beautiful utility as sparkling silver competes against hefty baryte?
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Tian, Can, Tang, Zhaohui, Xie, Yongfang, Zhang, Hu, Gui, Weihua (2023) Towards tailing grade prediction in zinc flotation via variablewise and temporalwise attention. Minerals Engineering, 192. 108000 doi:10.1016/j.mineng.2023.108000

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleTowards tailing grade prediction in zinc flotation via variablewise and temporalwise attention
JournalMinerals Engineering
AuthorsTian, CanAuthor
Tang, ZhaohuiAuthor
Xie, YongfangAuthor
Zhang, HuAuthor
Gui, WeihuaAuthor
Year2023 (February)Volume192
PublisherElsevier BV
DOIdoi:10.1016/j.mineng.2023.108000Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID15676077Long-form Identifiermindat:1:5:15676077:7
GUID0
Full ReferenceTian, Can, Tang, Zhaohui, Xie, Yongfang, Zhang, Hu, Gui, Weihua (2023) Towards tailing grade prediction in zinc flotation via variablewise and temporalwise attention. Minerals Engineering, 192. 108000 doi:10.1016/j.mineng.2023.108000
Plain TextTian, Can, Tang, Zhaohui, Xie, Yongfang, Zhang, Hu, Gui, Weihua (2023) Towards tailing grade prediction in zinc flotation via variablewise and temporalwise attention. Minerals Engineering, 192. 108000 doi:10.1016/j.mineng.2023.108000
In(2023) Minerals Engineering Vol. 192. Elsevier BV

See Also

These are possibly similar items as determined by title/reference text matching only.

Zhang, Hu, Tang, Zhaohui, Xie, Yongfang, Luo, Jin, Chen, Qing, Gui, Weihua (2021) Grade prediction of zinc tailings using an encoder-decoder model in froth flotation. Minerals Engineering, 172. 107173pp. doi:10.1016/j.mineng.2021.107173
Zhang, Hu, Tang, Zhaohui, Xie, Yongfang, Gao, Xiaoliang, Chen, Qing, Gui, Weihua (2021) Long short-term memory-based grade monitoring in froth flotation using a froth video sequence. Minerals Engineering, 160. 106677pp. doi:10.1016/j.mineng.2020.106677
Zhang, Jin, Tang, Zhaohui, Xie, Yongfang, Ai, Mingxi, Gui, Weihua (2020) Convolutional memory network-based flotation performance monitoring. Minerals Engineering, 151. 106332pp. doi:10.1016/j.mineng.2020.106332
Gao, Xiaoliang, Tang, Zhaohui, Xie, Yongfang, Zhang, Hu, Gui, Weihua (2021) A layered working condition perception integrating handcrafted with deep features for froth flotation. Minerals Engineering, 170. 107059pp. doi:10.1016/j.mineng.2021.107059
Zhong, Yuze, Tang, Zhaohui, Zhang, Hu, Xie, Yongfang, Guo, Juncen (2024) Short-long temporal graph convolution network for grade monitoring in a first zinc rougher. Minerals Engineering, 205. 108457 doi:10.1016/j.mineng.2023.108457
Xie, Yongfang, Zhang, Bin, Xie, Shiwen, Tang, Zhaohui (2024) Flotation froth image enhancement based on region decomposition and guided filtering. Minerals Engineering, 216. 108919 doi:10.1016/j.mineng.2024.108919
Cao, Binfang, Xie, Yongfang, Gui, Weihua, Wei, Lijun, Yang, Chunhua (2013) Integrated prediction model of bauxite concentrate grade based on distributed machine vision. Minerals Engineering, 53. 31-38 doi:10.1016/j.mineng.2013.07.003
Ai, Mingxi, Xie, Yongfang, Tang, Zhaohui, Zhang, Jin, Gui, Weihua (2021) Deep learning feature-based setpoint generation and optimal control for flotation processes. Information Sciences, 578. 644-658 doi:10.1016/j.ins.2021.07.060
Cen, Lihui, Wu, Yuming, Hu, Jian, Xia, E, Xie, Yongfang, Tang, Zhaohui (2022) Application of density-based clustering algorithm and capsule network to performance monitoring of antimony flotation process. Minerals Engineering, 184. 107603 doi:10.1016/j.mineng.2022.107603
Xu, Degang, Chen, Xiao, Xie, Yongfang, Yang, Chunhua, Gui, Weihua (2015) Complex networks-based texture extraction and classification method for mineral flotation froth images. Minerals Engineering, 83. 105-116 doi:10.1016/j.mineng.2015.08.017
Zhang, Jin, Tang, Zhaohui, Ai, Mingxi, Gui, Weihua (2018) Nonlinear modeling of the relationship between reagent dosage and flotation froth surface image by Hammerstein-Wiener model. Minerals Engineering, 120. 19-28 doi:10.1016/j.mineng.2018.01.018
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are Β© OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: September 5, 2025 03:37:35
Go to top of page