Vote for your favorite mineral in #MinCup25! - Dioptase vs. Wavellite
It's a green, green world for kiwi #wavellite vs desert emerald #dioptase.
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

Narmadhai, (2011) Analysis of Leakage Current to Predict Insulator Flashover Using Artificial Neural Network. Journal of Computer Science, 7. 167-172 doi:10.3844/jcssp.2011.167.172

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleAnalysis of Leakage Current to Predict Insulator Flashover Using Artificial Neural Network
JournalJournal of Computer Science
AuthorsNarmadhai, Author
Year2011 (February 1)Volume7
PublisherScience Publications
DOIdoi:10.3844/jcssp.2011.167.172Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID6670269Long-form Identifiermindat:1:5:6670269:4
GUID0
Full ReferenceNarmadhai, (2011) Analysis of Leakage Current to Predict Insulator Flashover Using Artificial Neural Network. Journal of Computer Science, 7. 167-172 doi:10.3844/jcssp.2011.167.172
Plain TextNarmadhai, (2011) Analysis of Leakage Current to Predict Insulator Flashover Using Artificial Neural Network. Journal of Computer Science, 7. 167-172 doi:10.3844/jcssp.2011.167.172
In(n.d.) Journal of Computer Science Vol. 7. Science Publications

See Also

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

Gunasekaran, (2011) Evaluation of Artificial Immune System with Artificial Neural Network for Predicting Bombay Stock Exchange Trends. Journal of Computer Science, 7. 967-972 doi:10.3844/jcssp.2011.967.972
Mehmood, (2010) Indoor Positioning System Using Artificial Neural Network. Journal of Computer Science, 6. 1219-1225 doi:10.3844/jcssp.2010.1219.1225
Chapram, (2012) Arabic Named Entity Recognition Using Artificial Neural Network. Journal of Computer Science, 8. 1285-1293 doi:10.3844/jcssp.2012.1285.1293
Santhanam, (2010) A Novel Approach to Classify Noises in Images Using Artificial Neural Network. Journal of Computer Science, 6. 506-510 doi:10.3844/jcssp.2010.506.510
Sivakumar, (2011) Adaptive Channel Equalization Using Multiplicative Neural Network for Rayleigh Faded Channel. Journal of Computer Science, 7. 1646-1651 doi:10.3844/jcssp.2011.1646.1651
Santhanam, (2011) An Efficient Weather Forecasting System using Radial Basis Function Neural Network. Journal of Computer Science, 7. 962-966 doi:10.3844/jcssp.2011.962.966
Durai, (2011) Content Based Image Retrieval using Novel Gaussian Fuzzy Feed Forward-Neural Network. Journal of Computer Science, 7. 958-961 doi:10.3844/jcssp.2011.958.961
Prasannamoorthy, (2011) Fault Detection and Classification in Power Electronic Circuits Using Wavelet Transform and Neural Network. Journal of Computer Science, 7. 95-100 doi:10.3844/jcssp.2011.95.100
Ibrahim, (2009) Artificial Neural Network Approach in Radar Target Classification. Journal of Computer Science, 5. 23-32 doi:10.3844/jcssp.2009.23.32
Abdullah, Daban Abdulsalam, Wakil, Karzan, H.H. Alshatri, Shwan (2020) Intelligent Attendance System Using Artificial Neural Network Based on Students’ Background. Journal of Computer Science, 16 (7) 1001-1009 doi:10.3844/jcssp.2020.1001.1009
Abdullah, Daban Abdulsalam, Wakil, Karzan, H.H. Alshatri, Shwan (2020) Intelligent Attendance System Using Artificial Neural Network Based on Students’ Background. Journal of Computer Science, 16 (7) 1001-1010 doi:10.3844/jcssp.2020.1001.1010
 
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: September 10, 2025 00:49:55
Go to top of page