Prediction of crude oil light end yields using neural network modeling.
Chung, Chee Kong.
Date of Issue2000
School of Electrical and Electronic Engineering
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.
DRNTU::Engineering::Computer science and engineering::Computing methodologies
Nanyang Technological University