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    Identification of Structural System Parameters Using the Cascade-Correlation Neural Network

    Source: Journal of Dynamic Systems, Measurement, and Control:;1994:;volume( 116 ):;issue: 004::page 790
    Author:
    H. Allison Smith
    ,
    J. Geoffrey Chase
    DOI: 10.1115/1.2899280
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The use of neural networks for structural system identification is receiving an increasing amount of attention through the research focused on structural control and intelligent systems. These systems require continuous monitoring and controlling of structural response; thus, on-line identification techniques are needed to provide real-time information about structural parameters. The Cascade-Correlation (Cascor) neural network is applied here to the structural system identification problem. The Cascor network utilizes a dynamic network architecture and a variable error threshold mechanism which facilitates training and can increase the network’s ability to generalize.
    keyword(s): Cascades (Fluid dynamics) , Artificial neural networks , Networks , Mechanisms AND Errors ,
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      Identification of Structural System Parameters Using the Cascade-Correlation Neural Network

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    http://yetl.yabesh.ir/yetl1/handle/yetl/113321
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    • Journal of Dynamic Systems, Measurement, and Control

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    contributor authorH. Allison Smith
    contributor authorJ. Geoffrey Chase
    date accessioned2017-05-08T23:43:43Z
    date available2017-05-08T23:43:43Z
    date copyrightDecember, 1994
    date issued1994
    identifier issn0022-0434
    identifier otherJDSMAA-26211#790_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/113321
    description abstractThe use of neural networks for structural system identification is receiving an increasing amount of attention through the research focused on structural control and intelligent systems. These systems require continuous monitoring and controlling of structural response; thus, on-line identification techniques are needed to provide real-time information about structural parameters. The Cascade-Correlation (Cascor) neural network is applied here to the structural system identification problem. The Cascor network utilizes a dynamic network architecture and a variable error threshold mechanism which facilitates training and can increase the network’s ability to generalize.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleIdentification of Structural System Parameters Using the Cascade-Correlation Neural Network
    typeJournal Paper
    journal volume116
    journal issue4
    journal titleJournal of Dynamic Systems, Measurement, and Control
    identifier doi10.1115/1.2899280
    journal fristpage790
    journal lastpage792
    identifier eissn1528-9028
    keywordsCascades (Fluid dynamics)
    keywordsArtificial neural networks
    keywordsNetworks
    keywordsMechanisms AND Errors
    treeJournal of Dynamic Systems, Measurement, and Control:;1994:;volume( 116 ):;issue: 004
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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