Metode Nonlinear Least Square (NLS) untuk Estimasi Parameter Model Wavelet Radial Basis Neural Network (WRBNN)
The use of wavelet radial basis model for forecasting nonlinear time series is introduced in this paper. The model is generated by artificial neural network approximation under restriction that the activation function on the hidden layers is radial basis. The current model is developed from the mult...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Diponegoro
2017-06-01
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| Series: | Media Statistika |
| Online Access: | https://ejournal.undip.ac.id/index.php/media_statistika/article/view/15601 |
| _version_ | 1818991841247232000 |
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| author | Rukun Santoso Sudarno Sudarno |
| author_facet | Rukun Santoso Sudarno Sudarno |
| author_sort | Rukun Santoso |
| collection | DOAJ |
| description | The use of wavelet radial basis model for forecasting nonlinear time series is introduced in this paper. The model is generated by artificial neural network approximation under restriction that the activation function on the hidden layers is radial basis. The current model is developed from the multiresolution autoregressives (MAR) model, with addition of radial basis function in the hidden layers. The power of model is compared to the other nonlinear model existed before, such as MAR model and Generalized Autoregressives Conditional Heteroscedastic (GARCH) model. The simulation data which be generated from GARCH process is applied to support the aim of research. The sufficiency of model is measured by sum squared of error (SSE). The computation results show that the proposed model has a power as good as GARCH model to carry on the heteroscedastic process.
Keywords:
Wavelet, Radial Basis, Heteroscedastic Model, Neural Network Model. |
| first_indexed | 2024-12-20T20:16:40Z |
| format | Article |
| id | doaj.art-1e1e8ee3ee4b496ebe9b2094e319a8b8 |
| institution | Directory Open Access Journal |
| issn | 1979-3693 2477-0647 |
| language | English |
| last_indexed | 2024-12-20T20:16:40Z |
| publishDate | 2017-06-01 |
| publisher | Universitas Diponegoro |
| record_format | Article |
| series | Media Statistika |
| spelling | doaj.art-1e1e8ee3ee4b496ebe9b2094e319a8b82022-12-21T19:27:42ZengUniversitas DiponegoroMedia Statistika1979-36932477-06472017-06-01101495910.14710/medstat.10.1.49-5911714Metode Nonlinear Least Square (NLS) untuk Estimasi Parameter Model Wavelet Radial Basis Neural Network (WRBNN)Rukun Santoso0Sudarno Sudarno1Departemen Statistika, Fakultas Sains dan Matematika, Universitas DiponegoroDepartemen Statistika, Fakultas Sains dan Matematika, Universitas DiponegoroThe use of wavelet radial basis model for forecasting nonlinear time series is introduced in this paper. The model is generated by artificial neural network approximation under restriction that the activation function on the hidden layers is radial basis. The current model is developed from the multiresolution autoregressives (MAR) model, with addition of radial basis function in the hidden layers. The power of model is compared to the other nonlinear model existed before, such as MAR model and Generalized Autoregressives Conditional Heteroscedastic (GARCH) model. The simulation data which be generated from GARCH process is applied to support the aim of research. The sufficiency of model is measured by sum squared of error (SSE). The computation results show that the proposed model has a power as good as GARCH model to carry on the heteroscedastic process. Keywords: Wavelet, Radial Basis, Heteroscedastic Model, Neural Network Model.https://ejournal.undip.ac.id/index.php/media_statistika/article/view/15601 |
| spellingShingle | Rukun Santoso Sudarno Sudarno Metode Nonlinear Least Square (NLS) untuk Estimasi Parameter Model Wavelet Radial Basis Neural Network (WRBNN) Media Statistika |
| title | Metode Nonlinear Least Square (NLS) untuk Estimasi Parameter Model Wavelet Radial Basis Neural Network (WRBNN) |
| title_full | Metode Nonlinear Least Square (NLS) untuk Estimasi Parameter Model Wavelet Radial Basis Neural Network (WRBNN) |
| title_fullStr | Metode Nonlinear Least Square (NLS) untuk Estimasi Parameter Model Wavelet Radial Basis Neural Network (WRBNN) |
| title_full_unstemmed | Metode Nonlinear Least Square (NLS) untuk Estimasi Parameter Model Wavelet Radial Basis Neural Network (WRBNN) |
| title_short | Metode Nonlinear Least Square (NLS) untuk Estimasi Parameter Model Wavelet Radial Basis Neural Network (WRBNN) |
| title_sort | metode nonlinear least square nls untuk estimasi parameter model wavelet radial basis neural network wrbnn |
| url | https://ejournal.undip.ac.id/index.php/media_statistika/article/view/15601 |
| work_keys_str_mv | AT rukunsantoso metodenonlinearleastsquarenlsuntukestimasiparametermodelwaveletradialbasisneuralnetworkwrbnn AT sudarnosudarno metodenonlinearleastsquarenlsuntukestimasiparametermodelwaveletradialbasisneuralnetworkwrbnn |