dc.contributor.author | Anisa | |
dc.contributor.author | Siswadi | |
dc.contributor.author | Budi suharjo | |
dc.contributor.author | Buldan Muslim | |
dc.date.accessioned | 2017-07-18T08:10:20Z | |
dc.date.available | 2017-07-18T08:10:20Z | |
dc.date.issued | 2006-01-12 | |
dc.identifier.citation | Jurnal Forum Pascasarjana Vol. 29, No. 1, Januari 2006 | id |
dc.identifier.issn | 0126-1886 | |
dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/87507 | |
dc.description.abstract | Radial basis function network, recognized as JFBR, is one of the methods or model used to predict any data or to classify the pattern and also is one of the methods of modeling and forecasting in neural network. JFBR is also a model which is used to overcome the probleme of unlinear and uncomplete data. This research aims to prdict the input- ouput parameter ionosfhere forF2 layar one day ahead for 1997-2003 data Sumedang, using JFBR by watching the accuration of fredictio, signed by small deviation value of MAD. | id |
dc.description.sponsorship | IPB | id |
dc.language.iso | id | id |
dc.publisher | Sekolah Pasca Sarjana IPB | id |
dc.relation.ispartofseries | Volume 29;No. 1, Hal. 37-51 | |
dc.subject.ddc | Penggunaan Jaringan Fungsi Basis Radial Pada Pemodelan Ionosfer Di Atas Sumedang | id |
dc.title | Penggunaan Jaringan Fungsi Basis Radial Pada Pemodelan Ionosfer Di Atas Sumedang | id |
dc.type | Article | id |
dc.subject.keyword | ionosphere, radial basis function network, prediction | id |