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    An Automated Machine Learning-Genetic Algorithm Framework With Active Learning for Design Optimization 

    Source: Journal of Energy Resources Technology:;2021:;volume( 143 ):;issue: 008:;page 082305-1
    Author(s): Owoyele, Opeoluwa; Pal, Pinaki; Vidal Torreira, Alvaro
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The use of machine learning (ML)-based surrogate models is a promising technique to significantly accelerate simulation-driven design optimization of internal combustion (IC) engines, due to the high computational cost of ...
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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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