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Title: Prediction of crude oil light end yields using neural network modeling
Authors: Chung, Chee Kong.
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies
Issue Date: 2000
Abstract: 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.
Schools: School of Electrical and Electronic Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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