Time Series Prediction Using Recurrent Neural Networks And Boosting: An Experimental Study In Pharmaceutical Product Formulation
Tesis ini berpusat pada perkembangan teknik Rangkaian Neural Buatan (ANN) dalam menyelesaikan masalah-masalah ramalan siri masa. Penyelidikan ini tertumpu kepada penggunaan·- rangkaian-rangkaian neural perulangan yang menyediakan satu kerangka yang menyeluruh bagi fonnulasi produk fannasi melalui...
| المؤلف الرئيسي: | |
|---|---|
| التنسيق: | أطروحة |
| اللغة: | الإنجليزية |
| منشور في: |
2002
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://eprints.usm.my/30471/ |
| Abstract | Abstract here |
| _version_ | 1854967130989002752 |
|---|---|
| author | Goh, Wei Yee |
| author_facet | Goh, Wei Yee |
| author_sort | Goh, Wei Yee |
| description | Tesis ini berpusat pada perkembangan teknik Rangkaian Neural Buatan (ANN)
dalam menyelesaikan masalah-masalah ramalan siri masa. Penyelidikan ini tertumpu
kepada penggunaan·- rangkaian-rangkaian neural perulangan yang menyediakan satu
kerangka yang menyeluruh bagi fonnulasi produk fannasi melalui pendekatan ramalan
siri masa. Khususnya, kerangka ini telah menjelajahi paradigma pembelajaran ANN
dalam mengendalikan perancangan eksperimen dan analisis. Berdasarkan kepada
kaedah-kaedah yang sedia ada, reka bentuk ANN yang baru dicadangkan untuk analisis
siri masa di dalam proses formulasi produk fannasi.
This thesis is devoted to the development of Artificial Neural Network (ANN)
techniques for solving time-series prediction problems. The research is focused on the
use of recurrent neural networks for devising a comprehensible framework for
pharmaceutical product formulation using time series prediction approach. In
particular, the framework explores the learning paradigms of ANNs for conducting the
experimental design and analysis. Based upon existing methodologies, novel ANN
architectures are proposed for time series analyses in the process of pharmac~utical
product formulation. |
| first_indexed | 2025-10-17T08:06:20Z |
| format | Thesis |
| id | usm-30471 |
| institution | Universiti Sains Malaysia |
| language | English |
| last_indexed | 2025-10-17T08:06:20Z |
| publishDate | 2002 |
| record_format | eprints |
| record_pdf | Abstract |
| spelling | usm-304712017-05-31T05:06:45Z http://eprints.usm.my/30471/ Time Series Prediction Using Recurrent Neural Networks And Boosting: An Experimental Study In Pharmaceutical Product Formulation Goh, Wei Yee TK1-9971 Electrical engineering. Electronics. Nuclear engineering Tesis ini berpusat pada perkembangan teknik Rangkaian Neural Buatan (ANN) dalam menyelesaikan masalah-masalah ramalan siri masa. Penyelidikan ini tertumpu kepada penggunaan·- rangkaian-rangkaian neural perulangan yang menyediakan satu kerangka yang menyeluruh bagi fonnulasi produk fannasi melalui pendekatan ramalan siri masa. Khususnya, kerangka ini telah menjelajahi paradigma pembelajaran ANN dalam mengendalikan perancangan eksperimen dan analisis. Berdasarkan kepada kaedah-kaedah yang sedia ada, reka bentuk ANN yang baru dicadangkan untuk analisis siri masa di dalam proses formulasi produk fannasi. This thesis is devoted to the development of Artificial Neural Network (ANN) techniques for solving time-series prediction problems. The research is focused on the use of recurrent neural networks for devising a comprehensible framework for pharmaceutical product formulation using time series prediction approach. In particular, the framework explores the learning paradigms of ANNs for conducting the experimental design and analysis. Based upon existing methodologies, novel ANN architectures are proposed for time series analyses in the process of pharmac~utical product formulation. 2002-05 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/30471/1/GOHWEIYEE.pdf Goh, Wei Yee (2002) Time Series Prediction Using Recurrent Neural Networks And Boosting: An Experimental Study In Pharmaceutical Product Formulation. Masters thesis, Universiti Sains Malaysia. |
| spellingShingle | TK1-9971 Electrical engineering. Electronics. Nuclear engineering Goh, Wei Yee Time Series Prediction Using Recurrent Neural Networks And Boosting: An Experimental Study In Pharmaceutical Product Formulation |
| title | Time Series Prediction Using Recurrent Neural Networks And Boosting: An Experimental Study In Pharmaceutical Product Formulation |
| title_full | Time Series Prediction Using Recurrent Neural Networks And Boosting: An Experimental Study In Pharmaceutical Product Formulation |
| title_fullStr | Time Series Prediction Using Recurrent Neural Networks And Boosting: An Experimental Study In Pharmaceutical Product Formulation |
| title_full_unstemmed | Time Series Prediction Using Recurrent Neural Networks And Boosting: An Experimental Study In Pharmaceutical Product Formulation |
| title_short | Time Series Prediction Using Recurrent Neural Networks And Boosting: An Experimental Study In Pharmaceutical Product Formulation |
| title_sort | time series prediction using recurrent neural networks and boosting an experimental study in pharmaceutical product formulation |
| topic | TK1-9971 Electrical engineering. Electronics. Nuclear engineering |
| url | http://eprints.usm.my/30471/ |
| work_keys_str_mv | AT gohweiyee timeseriespredictionusingrecurrentneuralnetworksandboostinganexperimentalstudyinpharmaceuticalproductformulation |