Vote for your favorite mineral in #MinCup25! - Chrysotile vs. Pectolite
Two new minerals to launch this year's cup! Hazardous (but useful!) chrysotile faces off against stunning gem pectolite.
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

Chen, J, Chen, H Y, Wen, M, Sun, S (2018) Industrial power demand forecasting based on big data technology orienting to energy internet: A case study of Hunan Province. IOP Conference Series: Earth and Environmental Science, 188. 12031pp. doi:10.1088/1755-1315/188/1/012031

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleIndustrial power demand forecasting based on big data technology orienting to energy internet: A case study of Hunan Province
JournalIOP Conference Series: Earth and Environmental Science
AuthorsChen, JAuthor
Chen, H YAuthor
Wen, MAuthor
Sun, SAuthor
Year2018 (October 30)Volume188
PublisherIOP Publishing
DOIdoi:10.1088/1755-1315/188/1/012031Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID9573806Long-form Identifiermindat:1:5:9573806:0
GUID0
Full ReferenceChen, J, Chen, H Y, Wen, M, Sun, S (2018) Industrial power demand forecasting based on big data technology orienting to energy internet: A case study of Hunan Province. IOP Conference Series: Earth and Environmental Science, 188. 12031pp. doi:10.1088/1755-1315/188/1/012031
Plain TextChen, J, Chen, H Y, Wen, M, Sun, S (2018) Industrial power demand forecasting based on big data technology orienting to energy internet: A case study of Hunan Province. IOP Conference Series: Earth and Environmental Science, 188. 12031pp. doi:10.1088/1755-1315/188/1/012031
In(2018) IOP Conference Series: Earth and Environmental Science Vol. 188. IOP Publishing


See Also

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

 
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 1, 2025 15:18:07
Go to top of page