Modeling Constructional Parameters of a Solid Oxide Fuel Cell by Using an Artificial Neural Network
Konrad Świrski , Jarosław Milewski
AbstractAn Artificial Neural Network (ANN) can predict an objects behavior with no algorithmic solution merely by utilizing available experimental data. The error backpropagation algorithm was used for an ANN training procedure. There are SOFC features mainly architectural in nature that cannot be expressed in numerical form or where numerical expression is difficult to obtain, i.e. electrolyte type, anode type, cathode type etc. In those situations a hybrid model (H-ANN) which contains the ANN model and mathematical expressions can be applied. The H-ANN is able to predict cell voltage with knowledge of minimum physical factors.
|Journal series||Applied Mechanics and Materials, ISSN 1662-7482|
|Keywords in English||artificial neutral network, contructional parameters|
|Score|| = 7.0, 26-11-2019, ArticleFromJournal|
= 7.0, 26-11-2019, ArticleFromJournal
|Publication indicators||= 2|
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