Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/36046
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dc.contributor.authorYang, Xuan Weien_US
dc.date.accessioned2010-04-23T02:25:12Z
dc.date.available2010-04-23T02:25:12Z
dc.date.copyright2007en_US
dc.date.issued2007
dc.identifier.urihttp://hdl.handle.net/10356/36046
dc.description92 p.en_US
dc.description.abstractThis research analyzes and evaluates the use of neural networks as a forecasting tool. Specifically a neural network's ability to predict the temperature offsets is tested. Temperature offsets are important control parameters in the semiconductor process. In the research, the neural network with back propagation learning algorithm is chosen to predict the temperature offsets based on the past observation. The prediction accuracy is compared against several forecasting methods, like multiple regression mode and radial basis function network.en_US
dc.subjectDRNTU::Engineering::Manufacturing
dc.titlePrediction of temperature offsets in the epitaxy processen_US
dc.typeThesisen_US
dc.contributor.supervisorZhong Zhaoweien_US
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.description.degreeMaster of Science (Computer Integrated Manufacturing)en_US
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