Foreign exchange prediction and trading using deep belief neural network

This project would provide an analysis on the deep belief network (DBN). A DBN would be constructed by stacking layers of restricted Boltzmann machines (RBM), and its learning process will be optimized by various optimization methods. Differing number of inputs, hidden layer and its number of neuron...

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Bibliographic Details
Main Author:	Muhammad Bin Mustaffa
Other Authors:	Wang Lipo
Format:	Final Year Project
Language:	English
Published:	2018
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:	http://hdl.handle.net/10356/76355
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-76355
record_format	dspace
spelling	sg-ntu-dr.10356-763552023-07-07T16:16:35Z Foreign exchange prediction and trading using deep belief neural network Muhammad Bin Mustaffa Wang Lipo School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems This project would provide an analysis on the deep belief network (DBN). A DBN would be constructed by stacking layers of restricted Boltzmann machines (RBM), and its learning process will be optimized by various optimization methods. Differing number of inputs, hidden layer and its number of neurons would also be implemented. A single exchange rate would be tested against a time period while three criteria would be considered to determine its performance. All this would be achieved by using a programming software called MATLAB. Bachelor of Engineering (Electrical and Electronic Engineering) 2018-12-20T02:35:25Z 2018-12-20T02:35:25Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/76355 en Nanyang Technological University 38 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Muhammad Bin Mustaffa Foreign exchange prediction and trading using deep belief neural network
description	This project would provide an analysis on the deep belief network (DBN). A DBN would be constructed by stacking layers of restricted Boltzmann machines (RBM), and its learning process will be optimized by various optimization methods. Differing number of inputs, hidden layer and its number of neurons would also be implemented. A single exchange rate would be tested against a time period while three criteria would be considered to determine its performance. All this would be achieved by using a programming software called MATLAB.
author2	Wang Lipo
author_facet	Wang Lipo Muhammad Bin Mustaffa
format	Final Year Project
author	Muhammad Bin Mustaffa
author_sort	Muhammad Bin Mustaffa
title	Foreign exchange prediction and trading using deep belief neural network
title_short	Foreign exchange prediction and trading using deep belief neural network
title_full	Foreign exchange prediction and trading using deep belief neural network
title_fullStr	Foreign exchange prediction and trading using deep belief neural network
title_full_unstemmed	Foreign exchange prediction and trading using deep belief neural network
title_sort	foreign exchange prediction and trading using deep belief neural network
publishDate	2018
url	http://hdl.handle.net/10356/76355
_version_	1772826488829116416

Foreign exchange prediction and trading using deep belief neural network

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