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dc.contributor.authorChiou, JCen_US
dc.contributor.authorYang, JYen_US
dc.date.accessioned2014-12-08T15:47:25Z-
dc.date.available2014-12-08T15:47:25Z-
dc.date.issued1998-11-01en_US
dc.identifier.issn0894-6507en_US
dc.identifier.urihttp://dx.doi.org/10.1109/66.728562en_US
dc.identifier.urihttp://hdl.handle.net/11536/31792-
dc.description.abstractA chemical vapor deposition (CVD) epitaxial deposition process modeling using fuzzy logic models (FLM's) has been proposed. The process modeling algorithm consists of a cluster estimation method and backpropagation algorithm to construct a number of modeling structures from the training data. A decision rule based on the multiple correlation factor is used to obtain the optimum structure of fuzzy model using the testing data. Upon the optimum structure has been reached, the gradient-descent method is used to refer the parameters of the final fuzzy model using both training and testing data. The algorithm has been applied to a nonlinear function and a vertical chemical vapor deposition process, The results demonstrate the efficiency and effectiveness of the proposed fuzzy logic model in comparison with existing fuzzy logic models and artificial neural network models.en_US
dc.language.isoen_USen_US
dc.subjectchemical vapor deposition (CVD) modelingen_US
dc.subjectclustering estimation methoden_US
dc.subjectfuzzy logicen_US
dc.titleA CVD epitaxial deposition in a vertical barrel reactor: Process modeling using cluster-based fuzzy logic modelsen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/66.728562en_US
dc.identifier.journalIEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURINGen_US
dc.citation.volume11en_US
dc.citation.issue4en_US
dc.citation.spage645en_US
dc.citation.epage653en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000076793200016-
dc.citation.woscount2-
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