Watch the Dallas Symposium LIVE, and fundraiser auction
Ticket proceeds support mindat.org! - click here...
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

Ataş, Musa, Yeşilnacar, Mehmet İrfan, Demir Yetiş, Ayşegül (2022) Novel machine learning techniques based hybrid models (LR-KNN-ANN and SVM) in prediction of dental fluorosis in groundwater. Environmental Geochemistry and Health, 44 (11) 3891-3905 doi:10.1007/s10653-021-01148-x

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleNovel machine learning techniques based hybrid models (LR-KNN-ANN and SVM) in prediction of dental fluorosis in groundwater
JournalEnvironmental Geochemistry and Health
AuthorsAtaş, MusaAuthor
Yeşilnacar, Mehmet İrfanAuthor
Demir Yetiş, AyşegülAuthor
Year2022 (November)Volume44
Issue11
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1007/s10653-021-01148-xSearch in ResearchGate
Generate Citation Formats
Mindat Ref. ID15480963Long-form Identifiermindat:1:5:15480963:8
GUID0
Full ReferenceAtaş, Musa, Yeşilnacar, Mehmet İrfan, Demir Yetiş, Ayşegül (2022) Novel machine learning techniques based hybrid models (LR-KNN-ANN and SVM) in prediction of dental fluorosis in groundwater. Environmental Geochemistry and Health, 44 (11) 3891-3905 doi:10.1007/s10653-021-01148-x
Plain TextAtaş, Musa, Yeşilnacar, Mehmet İrfan, Demir Yetiş, Ayşegül (2022) Novel machine learning techniques based hybrid models (LR-KNN-ANN and SVM) in prediction of dental fluorosis in groundwater. Environmental Geochemistry and Health, 44 (11) 3891-3905 doi:10.1007/s10653-021-01148-x
In(2022, November) Environmental Geochemistry and Health Vol. 44 (11) Springer Science and Business Media LLC

See Also

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

Yetiş, Recep, Atasoy, Ayşe Dilek, Demir Yetiş, Ayşegül, Yeşilnacar, Mehmet İrfan (2019) Hydrogeochemical characteristics and quality assessment of groundwater in Balikligol Basin, Sanliurfa, Turkey. Environmental Earth Sciences, 78 (11). doi:10.1007/s12665-019-8330-0
Yetis, Aysegul Demir, Yesilnacar, Mehmet Irfan, Atas, Musa (2021) A machine learning approach to dental fluorosis classification. Arabian Journal of Geosciences, 14 (2) doi:10.1007/s12517-020-06342-2
Yeşilnacar, Mehmet İrfan, Demir Yetiş, Ayşegül, Dülgergil, Çoruh Türksel, Kumral, Mustafa, Atasoy, Ayşe Dilek, Rastgeldi Doğan, Tuba, Tekiner, Sadık İsmail, Bayhan, İbrahim, Aydoğdu, Murat (2016) Geomedical assessment of an area having high-fluoride groundwater in southeastern Turkey. Environmental Earth Sciences, 75 (2). doi:10.1007/s12665-015-5002-6
Gbadebo, A. M. (2012) Groundwater fluoride and dental fluorosis in southwestern Nigeria. Environmental Geochemistry and Health, 34. 597-604 doi:10.1007/s10653-012-9455-1
Bech, Jaume (2022) Special Issue “Geochemistry, Soil Contamination and Human Health. Part 2.”. Environmental Geochemistry and Health, 44 (6) 1667-1671 doi:10.1007/s10653-021-01180-x
Bech, Jaume (2022) Soil contamination and human health: recent contributions. Environmental Geochemistry and Health, 44 (2) 295-300 doi:10.1007/s10653-021-01075-x
Panseriya, Haresh Z., Gavali, Deepa J., Lakhmapurkar, Jayendra J., Saha, Anuva, Gandhi, Priyal (2022) Water quality and probabilistic non-carcinogenic health risk of groundwater: a half decadal scenario change in Vadodara. Environmental Geochemistry and Health, 44 (11) 4091-4109 doi:10.1007/s10653-021-01156-x
Ayele, Biniyam A., Godebo, Tewodros Rango, Tekle-Haimanot, Redda, Yifru, Yared Mamushet (2022) Neuro-medical manifestations of fluorosis in populations living in the Main Ethiopian Rift Valley. Environmental Geochemistry and Health, 44 (3) 1129-1136 doi:10.1007/s10653-021-01016-8
Karunanidhi, D., Raj, M. Rhishi Hari, Roy, Priyadarsi D., Subramani, T. (2025) Integrated machine learning based groundwater quality prediction through groundwater quality index for drinking purposes in a semi-arid river basin of south India. Environmental Geochemistry and Health, 47 (4). doi:10.1007/s10653-025-02425-9
Panghal, Vishal, Sharma, Pawan, Mona, Sharma, Bhateria, Rachna (2022) Determining groundwater quality using indices and multivariate statistical techniques: a study of Tosham block, Haryana, India. Environmental Geochemistry and Health, 44 (10) 3581-3595 doi:10.1007/s10653-021-01120-9
Said, Ibrahim, Salman, Salman A., Elnazer, Ahmed A. (2022) Salinization of groundwater during 20 years of agricultural irrigation, Luxor, Egypt. Environmental Geochemistry and Health, 44 (11) 3821-3835 doi:10.1007/s10653-021-01135-2
 
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 © 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: August 24, 2025 12:02:15
Go to top of page