Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/76355
Title: Foreign exchange prediction and trading using deep belief neural network
Authors: Muhammad Bin Mustaffa
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Issue Date: 2018
Abstract: 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.
URI: http://hdl.handle.net/10356/76355
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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