Precious metal price prediction using deep neural networks
In the past, the value of gold was used to counterbalance the American dollar to secure its value under the American Bretton Wood system. Even today, the price of gold has undoubtedly shown to significantly impact the global economy and plenty of financial activities worldwide. Furthermore, with the...
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sg-ntu-dr.10356-1490102023-07-07T18:01:35Z Precious metal price prediction using deep neural networks Leow, Sean Teng Hui Wang Lipo School of Electrical and Electronic Engineering ELPWang@ntu.edu.sg Engineering::Electrical and electronic engineering In the past, the value of gold was used to counterbalance the American dollar to secure its value under the American Bretton Wood system. Even today, the price of gold has undoubtedly shown to significantly impact the global economy and plenty of financial activities worldwide. Furthermore, with the increasing adoption of deep learning, deep learning models have successfully demonstrated time s series forecasting in many different applications. The ability to predict the gold price accurately can offer a greater understanding of the fluctuations in prices. The project aims to implement a model that combines a Convolutional Neural Network (CNN) and Long-Short-Term Memory Neural Networks (LSTM) for its gold price prediction. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-05-24T12:42:32Z 2021-05-24T12:42:32Z 2021 Final Year Project (FYP) Leow, S. T. H. (2021). Precious metal price prediction using deep neural networks. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149010 https://hdl.handle.net/10356/149010 en A3277-201 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Leow, Sean Teng Hui Precious metal price prediction using deep neural networks |
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In the past, the value of gold was used to counterbalance the American dollar to secure its value under the American Bretton Wood system. Even today, the price of gold has undoubtedly shown to significantly impact the global economy and plenty of financial activities worldwide. Furthermore, with the increasing adoption of deep learning, deep learning models have successfully demonstrated time s series forecasting in many different applications. The ability to predict the gold price accurately can offer a greater understanding of the fluctuations in prices. The project aims to implement a model that combines a Convolutional Neural Network (CNN) and Long-Short-Term Memory Neural Networks (LSTM) for its gold price prediction. |
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Wang Lipo |
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Wang Lipo Leow, Sean Teng Hui |
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Final Year Project |
author |
Leow, Sean Teng Hui |
author_sort |
Leow, Sean Teng Hui |
title |
Precious metal price prediction using deep neural networks |
title_short |
Precious metal price prediction using deep neural networks |
title_full |
Precious metal price prediction using deep neural networks |
title_fullStr |
Precious metal price prediction using deep neural networks |
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Precious metal price prediction using deep neural networks |
title_sort |
precious metal price prediction using deep neural networks |
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Nanyang Technological University |
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2021 |
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https://hdl.handle.net/10356/149010 |
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