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    Modeling of an Intermediate Temperature Solid Oxide Fuel Cell Using the Adaptive Neuro-Fuzzy Inference System (ANFIS)

    Source: Journal of Fuel Cell Science and Technology:;2010:;volume( 007 ):;issue: 003::page 34501
    Author:
    Yasemin Vural
    ,
    Diyar Akay
    ,
    Mohamed Pourkashanian
    ,
    Derek B. Ingham
    DOI: 10.1115/1.3207873
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The modeling of an intermediate temperature solid oxide fuel cell using an adaptive neuro-fuzzy inference system (ANFIS) has been presented. The results show that a well trained and well tested ANFIS model has the capability to predict the fuel cell performance under varying operational conditions depending on the availability of the data and can be used as an alternative to the physical models in the sense that the results can be produced in a fast and cost effective way. The performance of the model in regions where there is data deficiency has been discussed.
    keyword(s): Temperature , Fuel cells , Modeling , Solid oxide fuel cells , Electric potential AND Flow (Dynamics) ,
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      Modeling of an Intermediate Temperature Solid Oxide Fuel Cell Using the Adaptive Neuro-Fuzzy Inference System (ANFIS)

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    http://yetl.yabesh.ir/yetl1/handle/yetl/143647
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    contributor authorYasemin Vural
    contributor authorDiyar Akay
    contributor authorMohamed Pourkashanian
    contributor authorDerek B. Ingham
    date accessioned2017-05-09T00:38:32Z
    date available2017-05-09T00:38:32Z
    date copyrightJune, 2010
    date issued2010
    identifier issn2381-6872
    identifier otherJFCSAU-28942#034501_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/143647
    description abstractThe modeling of an intermediate temperature solid oxide fuel cell using an adaptive neuro-fuzzy inference system (ANFIS) has been presented. The results show that a well trained and well tested ANFIS model has the capability to predict the fuel cell performance under varying operational conditions depending on the availability of the data and can be used as an alternative to the physical models in the sense that the results can be produced in a fast and cost effective way. The performance of the model in regions where there is data deficiency has been discussed.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleModeling of an Intermediate Temperature Solid Oxide Fuel Cell Using the Adaptive Neuro-Fuzzy Inference System (ANFIS)
    typeJournal Paper
    journal volume7
    journal issue3
    journal titleJournal of Fuel Cell Science and Technology
    identifier doi10.1115/1.3207873
    journal fristpage34501
    identifier eissn2381-6910
    keywordsTemperature
    keywordsFuel cells
    keywordsModeling
    keywordsSolid oxide fuel cells
    keywordsElectric potential AND Flow (Dynamics)
    treeJournal of Fuel Cell Science and Technology:;2010:;volume( 007 ):;issue: 003
    contenttypeFulltext
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