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    Hill Climbing Methods for the Optimization of Multiparameter Noise Disturbed Systems

    Source: Journal of Fluids Engineering:;1963:;volume( 085 ):;issue: 002::page 157
    Author:
    Harold J. Kushner
    DOI: 10.1115/1.3656551
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Modifications of the statistical technique of Stochastic Approximation are used as a means of experimentally optimizing multiparameter systems on which the only available information is obtained from noise perturbed samples of the performance. Varieties of both Gradient and Relaxation Processes are considered and methods are given for experimentally adjusting certain undetermined process constants for most rapid (mean square) convergence to the optimum parameter settings.
    keyword(s): Noise (Sound) , Optimization , Approximation , Gradients AND Relaxation (Physics) ,
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      Hill Climbing Methods for the Optimization of Multiparameter Noise Disturbed Systems

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    https://yetl.yabesh.ir/yetl1/handle/yetl/95478
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    contributor authorHarold J. Kushner
    date accessioned2017-05-08T23:12:43Z
    date available2017-05-08T23:12:43Z
    date copyrightJune, 1963
    date issued1963
    identifier issn0098-2202
    identifier otherJFEGA4-27249#157_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/95478
    description abstractModifications of the statistical technique of Stochastic Approximation are used as a means of experimentally optimizing multiparameter systems on which the only available information is obtained from noise perturbed samples of the performance. Varieties of both Gradient and Relaxation Processes are considered and methods are given for experimentally adjusting certain undetermined process constants for most rapid (mean square) convergence to the optimum parameter settings.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleHill Climbing Methods for the Optimization of Multiparameter Noise Disturbed Systems
    typeJournal Paper
    journal volume85
    journal issue2
    journal titleJournal of Fluids Engineering
    identifier doi10.1115/1.3656551
    journal fristpage157
    journal lastpage164
    identifier eissn1528-901X
    keywordsNoise (Sound)
    keywordsOptimization
    keywordsApproximation
    keywordsGradients AND Relaxation (Physics)
    treeJournal of Fluids Engineering:;1963:;volume( 085 ):;issue: 002
    contenttypeFulltext
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