Gold price prediction using long short-term memory neural network
Gold has always been valued throughout human history, playing a significant impact on the economy. There is a need to monitor gold prices as they are seen as good indicators for the economic market. The ability to predict future gold prices for investors and governments is important, as it helps...
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sg-ntu-dr.10356-1676492023-07-07T17:57:56Z Gold price prediction using long short-term memory neural network Ng, Nicholas Zheng Jie Wang Lipo School of Electrical and Electronic Engineering ELPWang@ntu.edu.sg Engineering::Electrical and electronic engineering Gold has always been valued throughout human history, playing a significant impact on the economy. There is a need to monitor gold prices as they are seen as good indicators for the economic market. The ability to predict future gold prices for investors and governments is important, as it helps them to make better investments and decisions for both the economy and the country. In recent years, the advancement of technology alongside machine learning has led to artificial intelligence(AI) that has superseded human capabilities. A subset of machine learning, called deep learning, allowed for the creation of newer neural networks and AI models such as Long Short-Term Memory (LSTM) that has seen success in time-series data prediction. This project uses inputs such as the historical price of gold, silver and crude oil in an LSTM model to effectively predict the price of gold. The model is also further subjected to variations in parameters to find the best possible setting which returns the most accurate predictions. This provided the parameters of 32 neurons in 2 hidden layers, a dropout rate of 0.2 in the first layer and 0.3 in the second layer, a window size of 80, a batch size of 16, 1000 epochs, and RMSProp optimizer for most ideal prediction. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-05-31T06:51:53Z 2023-05-31T06:51:53Z 2023 Final Year Project (FYP) Ng, N. Z. J. (2023). Gold price prediction using long short-term memory neural network. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167649 https://hdl.handle.net/10356/167649 en A3281-221 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Ng, Nicholas Zheng Jie Gold price prediction using long short-term memory neural network |
description |
Gold has always been valued throughout human history, playing a significant impact on the
economy. There is a need to monitor gold prices as they are seen as good indicators for the
economic market. The ability to predict future gold prices for investors and governments is
important, as it helps them to make better investments and decisions for both the economy and
the country.
In recent years, the advancement of technology alongside machine learning has led to artificial
intelligence(AI) that has superseded human capabilities. A subset of machine learning, called
deep learning, allowed for the creation of newer neural networks and AI models such as Long
Short-Term Memory (LSTM) that has seen success in time-series data prediction.
This project uses inputs such as the historical price of gold, silver and crude oil in an LSTM
model to effectively predict the price of gold. The model is also further subjected to variations in
parameters to find the best possible setting which returns the most accurate predictions. This
provided the parameters of 32 neurons in 2 hidden layers, a dropout rate of 0.2 in the first layer
and 0.3 in the second layer, a window size of 80, a batch size of 16, 1000 epochs, and RMSProp
optimizer for most ideal prediction. |
author2 |
Wang Lipo |
author_facet |
Wang Lipo Ng, Nicholas Zheng Jie |
format |
Final Year Project |
author |
Ng, Nicholas Zheng Jie |
author_sort |
Ng, Nicholas Zheng Jie |
title |
Gold price prediction using long short-term memory neural network |
title_short |
Gold price prediction using long short-term memory neural network |
title_full |
Gold price prediction using long short-term memory neural network |
title_fullStr |
Gold price prediction using long short-term memory neural network |
title_full_unstemmed |
Gold price prediction using long short-term memory neural network |
title_sort |
gold price prediction using long short-term memory neural network |
publisher |
Nanyang Technological University |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/167649 |
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1772825398936076288 |