A model for predicting the Ms temperatures of steels.

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3190

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DC Field	Value	Language
dc.creator	Sourmail, T.	-
dc.creator	García Mateo, Carlos	-
dc.date	2008-03-10T14:47:43Z	-
dc.date	2008-03-10T14:47:43Z	-
dc.date	2005	-
dc.date.accessioned	2017-01-31T01:00:38Z	-
dc.date.available	2017-01-31T01:00:38Z	-
dc.identifier	Computational Materials Science 34 (2005) 213–218	-
dc.identifier	http://hdl.handle.net/10261/3190	-
dc.identifier	10.1016/j.commatsci.2005.01.001	-
dc.identifier.uri	http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3190	-
dc.description	Using neural networks in a Bayesian framework, a model has been derived for the Ms temperature of steels over a wide range of compositions. By its design and by use of a more extensive database, this model improves over existing ones, by its accuracy and its ability to avoid wild predictions.	-
dc.description	NPL for provision of MTDATA and Neuromat for provision of the Model Manager.	-
dc.description	Peer reviewed	-
dc.format	118229 bytes	-
dc.format	application/pdf	-
dc.language	eng	-
dc.publisher	Elsevier	-
dc.relation	http://dx.doi.org/10.1016/j.commatsci.2005.01.001	-
dc.rights	openAccess	-
dc.subject	Martensite; Thermodynamics; Bayesian neural networks; Linear regression	-
dc.title	A model for predicting the Ms temperatures of steels.	-
dc.type	Artículo	-
Appears in Collections:	Digital Csic

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