Abstract
In this paper, we introduce an automatic classification approach based on combining two algorithms. One of them belongs to Neural Networks approach and the second is based on Multivariate Statistical approach. In this study we will present two algorithms their relative strengths and weaknesses. We realize that these two methods can complement one another resulting in better decision support system. Integrating these complementary features is one way to develop hybrid system that could overcome the limitations of individual solution strategies. We evaluate this hybrid system on data provided by semiconductor fab, especially on Parametric Tests (PT) data. This procedure was successfully validated at PT data provided by STMicroelectronics - Rousset fab.
Original language | English |
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Pages | 125-130 |
Number of pages | 6 |
Publication status | Published - 2007 |
Event | 3rd International Conference on Advances in Vehicle Control and Safety 2007, AVCS 2007 and 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007, Held at the IMSM 2007 - Buenos Aires, Argentina Duration: Feb 8 2007 → Feb 10 2007 |
Other
Other | 3rd International Conference on Advances in Vehicle Control and Safety 2007, AVCS 2007 and 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007, Held at the IMSM 2007 |
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Country/Territory | Argentina |
City | Buenos Aires |
Period | 2/8/07 → 2/10/07 |
Keywords
- GRLVQ
- Parametric tests
ASJC Scopus subject areas
- Automotive Engineering
- Control and Systems Engineering
- Safety, Risk, Reliability and Quality