In this thesis, three methods are presented to model the decision process of whether
or not to bid for a tender in offshore petroleum platform fabrication. A sample data and
the assessment based on this data are gathered from an offshore petroleum platform
fabrication company and this information is analyzed to understand the significant
parameters in the industry.
The alternative methods, &ldquo / Regression Analysis&rdquo / , &ldquo / Neural Network Method&rdquo / and &ldquo / Fuzzy
Neural Network Method&rdquo / , are used for modeling of the bidding decision process. The
regression analysis examines the data statistically where the neural network method
and fuzzy neural network method are based on artificial intelligence. The models are
developed using the bidding data compiled from the offshore petroleum platform
fabrication projects. In order to compare the prediction performance of these methods
&ldquo / Cross Validation Method&rdquo / is utilized.
The models developed in this study are compared with the bidding decision method
used by the company. The results of the analyses show that regression analysis and
neural network method manage to have a prediction performance of 80% and fuzzy neural network has a prediction performance of 77,5% whereas the method used by
the company has a prediction performance of 47,5%. The results reveal that the
suggested models achieve significant improvement over the existing method for
making the correct bidding decision.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12610820/index.pdf |
| Date | 01 August 2009 |
| Creators | Sozgen, Burak |
| Contributors | Sonmez, Rifat |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
Page generated in 0.0085 seconds