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dc.contributor.authorChung, Chee Kong.en_US
dc.description.abstractThe objective of the project is to explore the feasibility of using neural network modeling technique to predict the yields of light hydrocarbon (specifically propane and butane) in crude oil, using easily measurable crude oil properties, such as specific gravity (S.G.) and yields of the various crude oil fractions. Another objective of this project is to compare the effectiveness of using neural network modeling technique to that achieved using multi-linear regression.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies-
dc.titlePrediction of crude oil light end yields using neural network modelingen_US
dc.contributor.supervisorChan, Sai Piuen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Computer Control and Automation)en_US
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