Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/149010
Title: Precious metal price prediction using deep neural networks
Authors: Leow, Sean Teng Hui
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Publisher: Nanyang Technological University
Source: 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
Project: A3277-201
Abstract: 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.
URI: https://hdl.handle.net/10356/149010
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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