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Surrogate Model-Based Engineering Design and Optimization

Bag om Surrogate Model-Based Engineering Design and Optimization

This book covers some of the most popular methods in design space sampling, ensembling surrogate models, multi-fidelity surrogate model construction, surrogate model selection and validation, surrogate-based robust design optimization, and surrogate-based evolutionary optimization. Surrogate or metamodels are now frequently used in complex engineering product design to replace expensive simulations or physical experiments. They are constructed from available input parameter values and the corresponding output performance or quantities of interest (QOIs) to provide predictions based on the fitted or interpolated mathematical relationships. The book highlights a range of methods for ensembling surrogate and multi-fidelity models, which offer a good balance between surrogate modeling accuracy and building cost. A number of real-world engineering design problems, such as three-dimensional aircraft design, are also provided to illustrate the ability of surrogates for supporting complex engineering design. Lastly, illustrative examples are included throughout to help explain the approaches in a more "hands-on" manner.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9789811507304
  • Indbinding:
  • Hardback
  • Sideantal:
  • 240
  • Udgivet:
  • 15. november 2019
  • Udgave:
  • 12020
  • Størrelse:
  • 155x235x0 mm.
  • Vægt:
  • 547 g.
  • BLACK NOVEMBER
  Gratis fragt
Leveringstid: 8-11 hverdage
Forventet levering: 29. november 2024

Beskrivelse af Surrogate Model-Based Engineering Design and Optimization

This book covers some of the most popular methods in design space sampling, ensembling surrogate models, multi-fidelity surrogate model construction, surrogate model selection and validation, surrogate-based robust design optimization, and surrogate-based evolutionary optimization.
Surrogate or metamodels are now frequently used in complex engineering product design to replace expensive simulations or physical experiments. They are constructed from available input parameter values and the corresponding output performance or quantities of interest (QOIs) to provide predictions based on the fitted or interpolated mathematical relationships.
The book highlights a range of methods for ensembling surrogate and multi-fidelity models, which offer a good balance between surrogate modeling accuracy and building cost. A number of real-world engineering design problems, such as three-dimensional aircraft design, are also provided to illustrate the ability of surrogates for supporting complex engineering design. Lastly, illustrative examples are included throughout to help explain the approaches in a more "hands-on" manner.

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