The GMDH model and its application to forecating of rice yields
In this paper, the group method of handling (GMDH) model and their application to the forecasting of the rice yields time series are described. The use of such GMDH leads to successful application in broad range of areas. However, in some fields, such as rice yields forecasting, the use GMDH is stil...
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| Language: | en |
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2008
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| Online Access: | http://eprints.utm.my/8533/1/RuhaidahSamsudin2008_TheGmdhModelAndItsApplication.pdf http://eprints.utm.my/8533/ |
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| author | Samsudin, Ruhaidah Saad, Puteh Shabri, Ani |
| author_facet | Samsudin, Ruhaidah Saad, Puteh Shabri, Ani |
| author_sort | Samsudin, Ruhaidah |
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| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | In this paper, the group method of handling (GMDH) model and their application to the forecasting of the rice yields time series are described. The use of such GMDH leads to successful application in broad range of areas. However, in some fields, such as rice yields forecasting, the use GMDH is still scare. At1ificial neural networks (ANN) have been shown to be powerful tools for system modeling. This study addressed the question of whether GMDH could be used to estimate more accurate in modeling and forecasting compared with the ANN model. To assess the effectiveness of these models, we used 9 years of time series records for rice yield data in Malaysia from 1995 to 200 I. The results demonstrate that GMDH model is superior to the ANN for rice yield forecasting. |
| format | Article |
| id | my.utm.eprints-8533 |
| institution | Universiti Teknologi Malaysia |
| language | en |
| publishDate | 2008 |
| publisher | Penerbit UTM Press |
| record_format | eprints |
| spelling | my.utm.eprints-85332017-11-01T04:17:24Z http://eprints.utm.my/8533/ The GMDH model and its application to forecating of rice yields Samsudin, Ruhaidah Saad, Puteh Shabri, Ani QA75 Electronic computers. Computer science In this paper, the group method of handling (GMDH) model and their application to the forecasting of the rice yields time series are described. The use of such GMDH leads to successful application in broad range of areas. However, in some fields, such as rice yields forecasting, the use GMDH is still scare. At1ificial neural networks (ANN) have been shown to be powerful tools for system modeling. This study addressed the question of whether GMDH could be used to estimate more accurate in modeling and forecasting compared with the ANN model. To assess the effectiveness of these models, we used 9 years of time series records for rice yield data in Malaysia from 1995 to 200 I. The results demonstrate that GMDH model is superior to the ANN for rice yield forecasting. Penerbit UTM Press 2008 Article PeerReviewed application/pdf en http://eprints.utm.my/8533/1/RuhaidahSamsudin2008_TheGmdhModelAndItsApplication.pdf Samsudin, Ruhaidah and Saad, Puteh and Shabri, Ani (2008) The GMDH model and its application to forecating of rice yields. Jurnal Teknologi Maklumat, 20 (4). pp. 113-123. ISSN 0128-3790 |
| spellingShingle | QA75 Electronic computers. Computer science Samsudin, Ruhaidah Saad, Puteh Shabri, Ani The GMDH model and its application to forecating of rice yields |
| title | The GMDH model and its application to forecating of rice yields
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| title_full | The GMDH model and its application to forecating of rice yields
|
| title_fullStr | The GMDH model and its application to forecating of rice yields
|
| title_full_unstemmed | The GMDH model and its application to forecating of rice yields
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| title_short | The GMDH model and its application to forecating of rice yields
|
| title_sort | gmdh model and its application to forecating of rice yields |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/8533/1/RuhaidahSamsudin2008_TheGmdhModelAndItsApplication.pdf http://eprints.utm.my/8533/ |
| url_provider | http://eprints.utm.my/ |