Prediction of crude oil light end yields using neural network modeling

The 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 cru...

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Bibliographic Details
Main Author: Chung, Chee Kong.
Other Authors: Chan, Sai Piu
Format: Theses and Dissertations
Published: 2008
Subjects:
Online Access:http://hdl.handle.net/10356/4187
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Institution: Nanyang Technological University
Description
Summary:The 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.