Artificial Neural Network Based Model for Calculating the Flow Composition Influence of Solid Oxide Fuel Cell

dc.contributor.author	Milewski, Jaros‚aw
dc.contributor.author	ڑwirski, Konrad
dc.date.accessioned	2017-05-09T01:08:59Z
dc.date.available	2017-05-09T01:08:59Z
dc.date.issued	2014
dc.identifier.issn	2381-6872
dc.identifier.other	fc_011_02_021001.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl/handle/yetl/155110
dc.description.abstract	The paper presents use of an artificial neural network (ANN) for predicting the thermalflow behavior of a solid oxide fuel cell with no algorithmic solution merely by utilizing available experimental data. The error backpropagation algorithm was used for an ANN training procedure.
dc.publisher	The American Society of Mechanical Engineers (ASME)
dc.title	Artificial Neural Network Based Model for Calculating the Flow Composition Influence of Solid Oxide Fuel Cell
dc.type	Journal Paper
dc.journal.volume	11
dc.journal.issue	2
dc.journal.title	Journal of Fuel Cell Science and Technology
dc.identifier.doi	10.1115/1.4025922
dc.journal.fristpage	21001
dc.journal.lastpage	21001
dc.identifier.eissn	2381-6910
dc.tree	Journal of Fuel Cell Science and Technology:;2014:;volume( 011 ):;issue: 002
dc.contenttype	Fulltext